Sisymbrium officinale (L.) Scop. is a wild common plant of the Brassicaceae family. It is known as “the singers’ plant” for its traditional use in treating aphonia and vocal disability. Despite its wide use in herbal preparations, the molecular mechanism of action of S. officinale extracts is not known. The plant is rich in glucosinolates and isothiocyanates, which are supposed to be its active compounds. Some members of this family, in particular allylisothiocyanate, are strong agonists of the transient receptor potential ankyrin 1 (TRPA1) channel, which is involved in the somatosensory perception of pungency as well as in the nociception pathway of inflammatory pain. This study aims to isolate the glucosinolates and isothiocianates from fresh S. officinale to identify the major components and test their activity in in vitro assays with a cloned TRPA1 channel. Samples of cultivated S. officinale have been extracted and the active compounds isolated by column chromatography, HPLC and PTLC. The main components glucoputranjivin, isopropylisothiocyanate and 2-buthylisothiocianate have been tested on TRPA1. The glucosinolates glucoputranjivin and sinigrin turned out to be inactive, while isopropylisothiocyanate and 2-buthylisothiocyanate are potent agonists of TRPA1, with an EC50 in the range of the high potency natural agonists identified so far for this somatosensory channel. Sisymbrium officinale (L.) Scop. (Brassicaceae) (SO) is an annual plant which is spread mostly in the Eurasiatic Region and North Africa. It is very common in bare ground, on roadsides, dumps and on the edges of fields. The plant is the object of a multidisciplinary project named “Erisimo a Milano” studying its diffusion and ecology in North Italy, agronomic potential, phytochemistry and food applications i) were determined using the selective intracellular fluorescent probe Fluo-4. Assays of the rat TRPA1-mediated elevation of intracellular Ca2+ in transfected HEK-293 cells were performed as described i in not-transfected HEK-293 cells were used as a baseline and subtracted from the values obtained from transfected cells. Agonist efficacy was expressed as a percentage of the effect on [Ca2+]i observed with 100 μM allylisothiocyanate (AITC). The potency of the compounds  was determined as the concentration required to produce half-maximal increases in [Ca2+]i. Antagonist/desensitizing behavior as evaluated against TRPA1 agonist AITC 100 μM by adding the compound directly into the quartz cuvette 5 min before the stimulation of cells with the agonist. IC50 is expressed as the concentration exerting a half-maximal inhibition of an agonist effect, taking as 100% the effect on [Ca2+]i exerted by the agonist alone. Dose–response curves are fitted by a sigmoidal regression with a variable slope. Curve fitting and parameter estimation were performed with a GraphPad Prism . Three independent experiments were done for each determination; all determinations were performed at least in triplicate. The time-course spectra showing the increase of intracellular Ca2+ upon application of the compounds are available in Compound effects on intracellular Caescribed . Briefly


The ICON6 trial (ISRCTN68510403) is a phase III academic-led, international,randomized, three-arm, double-blind, placebo-controlled trial of theaddition of cediranib to chemotherapy in recurrent ovarian cancer. Itinvestigated the use of placebo during chemotherapy and maintenance (arm A),cediranib alongside chemotherapy followed by placebo maintenance (arm B) andcediranib throughout both periods (arm C). Results of the primary comparisonshowed a meaningful gain in progression-free survival (time to progressionor death from any cause) when comparing arm A (placebo) with arm C(cediranib). As a consequence of the positive results, AstraZeneca wasengaged with the Medical Research Council trials unit to discuss regulatorysubmission using ICON6 as the single pivotal trial.A relatively limited level of on-site monitoring, single data entry andinvestigator’s local evaluation of progression were used on trial. In orderto submit a license application, it was decided that (a) extensiveretrospective source data verification of medical records against casereport forms should be performed, (b) further quality control checks foraccuracy of data entry should be performed and (c) blinded independentcentral review of images used to define progression should be undertaken. Toassess the value of these extra activities, we summarize the impact on bothefficacy and safety outcomes.Data point changes were minimal; those key to the primary results had a 0.47%error rate (36/7686), and supporting data points had a 0.18% error rate. The impact of the source data verification and quality controlprocesses were analyzed jointly. The conclusion drawn for the primaryoutcome measure of progression-free survival between arm A and arm C wasunchanged. The log-rank test p-value changed only at the sixth decimalplace, the hazard ratio does not change from 0.57 with the exception of amarginal change in its upper bound (0.74–0.73) and the medianprogression-free survival benefit from arm C remained at 2.4 months.Separately, the blinded independent central review of progression scans wasperformed as a sensitivity analysis. Estimates and p values varied slightlybut overall demonstrated a difference in arms, which is consistent with theinitial result. Some increases in toxicity were observed, though these weregenerally minor, with the exception of hypertension. However, none of theseincreases were systematically biased toward one arm.The conduct of this pragmatic, academic-sponsored trial was sufficient giventhe robustness of the results, shown by the results remaining largelyunchanged following retrospective verification despite not being designedfor use in a marketing authorization. The burden of such comprehensiveretrospective effort required to ensure the results of ICON6 were acceptableto regulators is difficult to justify. The extent of data verification conducted on a trial led by a pharmaceutical companywith a marketing authorization in mind and one conducted more pragmatically with afocus principally on the advancement of knowledge of the intervention can divergesubstantially. Usually this is a practical decision driven by its feasibility asextensive verification of data is costly with only limited value to academicsponsors.Online Appendix). The trial had enrolled fewer than 390 patients(from a planned 2000) when drug supply availability drove a redesign and prematuretermination of recruitment.The ICON6 trial (NCT00532194) is an academic-led, randomized phase III clinical trialinvestigating the use of cediranib  in addition to a standard chemotherapy regimenin relapsed ovarian cancer. This UK Medical Research Council–sponsored trial wasconducted pragmatically, allowing investigator-choice chemotherapy and delegatingroles and responsibilities for conduct and regulation to each of the fourinternational collaborative groups. These groups were the UK Medical ResearchCouncil-National Cancer Research Institute, Canadian Cancer Trials Group, AustraliaNew Zealand Gynecological Oncology Group and Grupo Español de Investigación enCáncer de Ovario. The trial was centrally coordinated by the Medical ResearchCouncil Clinical Trials Unit at University College London (the “Unit”). Centralizedrisk-based monitoring was used in a proactive manner throughout the conduct of ICON6with, for example, consent and eligibility checks, database plausibility algorithmsand triggered for-cause site visits (see full details in the Patients were randomized to receive one of three arms: chemotherapy with placebothroughout (arm A); chemotherapy with concurrent cediranib, followed by placeboduring a maintenance period (arm B); and chemotherapy with concurrent cediranib,followed by maintenance cediranib (arm C). This trial design is shown in 13 This meant areduction in the target sample size of ICON6 to approximately 470 patients owing tothe very limited remaining supply of the drug, and a reconfiguration of the primarycomparison to maintain as much power as possible with the much smaller sample size.The primary outcome was swapped from overall survival to the more frequent, andearlier occurring, measure of progression-free survival . The primary comparison was also revised from armsA versus B versus C to only compare arms A versus C which was considered the mostappropriate comparison to target in view of emerging data for concurrent andmaintenance bevacizumab. It is important to note that this change of primary outcomewas made before any interim analysis was performed of efficacy outcome measures.While ICON6 was still accruing patients, AstraZeneca discontinued manufacturing thedrug, following evidence from other randomized clinical trials that cediranib wasnot effective in several tumor types .The Lancet in 2016.5Results of the pre-specified primary analysis showed clear evidence of an improvementin progression-free survival with a hazard ratio of 0.57  and a 2.3 month improvement in the differencebetween the median time before the cancer returned (arm C vs arm A). Thisimprovement from 8.7 to 11.1 months in the median time to progression or death fromany cause would be considered by many to be a clinically meaningful improvement inrelapsed ovarian cancer, a setting where patients receive diminishing absolutebenefit from each subsequent treatment regimen post-progression and the duration ofthe response is short, although this benefit came with added toxic effects. Thesetrial results were initially presented at the Presidential Session of the EuropeanCancer Congress in 2013 and later, after the work described here, published in6 The lack of benefit seen in other tumor types meant that, despite its limitedsize, ICON6 would be the single pivotal randomized phase III trial in thesubmission. It was to be supported by NCI 8348 that a randomized phase II trial in90 patients demonstrates a progression-free survival improvement for cediranib plusolaparib over olaparib alone in the same setting of relapsed ovariancancer.8ICON6 had been conducted using a long-established risk-based monitoring approachthat is common in clinical trials sponsored by our academic Unit and is consistentwith recent approaches advocated by EMA/FDA.9 However, this is very different to typical company-sponsored monitoringpractices and in any case, plans for on-site monitoring in ICON6 had been weightedtoward triggered for-cause visits in the middle to later stages of the trial, so hadbeen infrequent at the time recruitment was prematurely terminated. Consequently,the trial team in conjunction with AstraZeneca instigated a retrospective dataverification process. Retrospective data verification was undertaken within threebroad themes of source data verification, quality control checks and blindedindependent central review of scans as it was judged that the regulator wouldrequire such processes. In this article, we report the impact of these verificationprocesses on the key efficacy and safety results.As a consequence of the results of ICON6, AstraZeneca restarted drug manufacturingand initiated preparation of a marketing authorization application, initially in theEuropean Union with the European Medicines Agency (EMA), and also potentially in theUnited States with a submission to the Food and Drug Administration (FDA).After presentation of the primary results, the Unit and AstraZeneca agreed how ICON6might be prepared to be the pivotal trial within a regulatory submission. Key areas,and our proposed actions, were as follows: (a) source data verification—checking ofthe completed paper case report forms against the source patient notes at site; (b)quality control checks—verification of the data entry of the paper forms onto thetrials unit’s database; (c) blinded independent central review—independentreassessment of the patient’s locally held tumor scans to adjudicate the time pointof progressive disease.4All analyses retained the same data freeze date of 19 April 2013, with only dataprior to this cut-off contributing to the primary analysis. This revised databasewas used to assess changes in the primary outcome progression-free survival, and thefour key toxicities emphasized in the initial presentation due to the nature of thisclass of drug.Online Appendix.Centralized monitoring based on set risk factors was planned to be usedthroughout the trial but supplemented with on-site visits of all UK sites atleast once during the course of the trial in addition to any triggered visit.However, as the trial was shortened due to drug supply, this was not possible.Details of the monitoring plan, and updates to it, is given in the Checking visits for retrospective source data verification were fulfilled by athird-party contract research organization arranged by AstraZeneca across allcountries over the space of 7 months. This typically involved two clinicalresearch associates visiting each site for 1–2 days and totaling 594 visits.This required a large amount of coordination both at the Unit and at theindividual sites, because sites had to retrieve the relevant patient notes andthe completed trial forms prior to each visit. During source data verification,the form used was compared against the patient notes. Any discrepancies betweenthe source patient hospital notes and the form were documented. Thesediscrepancies were then resolved by the site via corrective action on a DataClarification Form or the completion of a new form, which was then sent to theUnit for data entry.Online Appendix.This process of comparing the source notes and the form was completed for datacritical to the reporting of the trial’s key outcome measures. These dataincluded select fields of the screening, final safety visit, follow-up andprogression forms, and all data on the tumor assessment, adverse event (AE),serious adverse event (SAE), end of trial drug summary and death forms. Furtherdetail is given in the 11 Whereas for manycompany-sponsored studies double data entry would be used.Quality control checks were performed to ensure that the data entered on to theUnit’s database accurately represented the completed form sent from the site.This process was deemed prudent as the Unit used trained single data entry asper local policy. The Unit’s policy of trained single data entry is based on theconclusion that when automatic database validation checks and statistical errorchecking are used, there is only a small marginal gain in accuracy from doublingof the data entry time and cost.This second aspect of checking was initiated once the source data verificationwas completed with all queries resolved and closed, and any new forms enteredonto the database. The data extracted was compared to a scanned copy of thepaper form and any related documentation. A quality control error was defined asany difference between the form and the study database where there was nosupporting documentation for the inconsistency. The error rate was calculatedusing the total number of valid, newly reported discrepancies divided by thetotal number of data points checked.Key data—data pointscritical to the primary efficacy analysis were examined for errors in all 486patients and (b) Supporting data—data points contributing tothe detailed reporting of the trial were examined for errors in 25 of 486patients (5% sample).The process of checking the form against the database comprised two distinctcomponents, performed in parallel: (a) key data by the Trial Management Teamand so checked for all patients were as follows:Data points deemed to be Screening form—date of randomizationFollow-up form—survival status, date last seen aliveProgression form—date of progressionDeath form—date of deathSAE form—main symptom, grade, date of onset, causal relationship to SAE,expectedness, action taken due to SAEsupporting data were more extensive andthe same as reviewed in the source data verification, these are describedfurther in the Online Appendix. The 5% sample of patients consisted of twopatients from each of the five highest recruiting sites in the United Kingdom;plus 12 patients from the remainder of the UK sites (22 of 380 UK recruitedpatients); and one patient randomly selected from each of the non-UKcollaborating nations, Canada, Australia and Spain, who recruited, respectively,87, 17 and 2 patients. An initial 5% sample of patients, expanded if deemednecessary, was done to ease the burden on sites given the age of the trial andthe retrospective nature of the verification.Data points deemed to be key data errors, an error rate of>0.5% 12 would signal issues with the trial conduct and for supportingdata errors, it would warrant further investigation with checkingpromptly expanded into 100% of trial participants. All errors identified in thecourse of both quality control processes were corrected.It was decided that for 14 Slightdifferences were anticipated as reviewing scans is subjective to an extent, andwithin the trial investigators could also declare progression based on “generaldeterioration” alone.Blinded independent central review was coordinated by AstraZeneca using aspecialist contract research organization to assess the study imaging and todetermine an overall cancer tumor assessment at each visit using RECIST criteria.Unlike source data verification and quality control, the blinded independentcentral review was a sensitivity analysis of the primary efficacy outcome rather than a refinement. The blinded independentcentral review analysis subset, limited to patients who had at least one scan orradiological report provided for review, was used to assess ascertainment biasand comprised 96% of the all patients randomized intention-to-treatpopulation.There was a minimum of six independent, qualified, board-eligible radiologistsassigned to the evaluation. These reviewers assessed the study imaging todetermine overall tumor assessment at each time point using RECIST criteria.Each patient’s data was reviewed blinded to treatment allocation by tworeviewers using two methods: (a) primary review of each patient’s tumorassessment at each time point and (b) global review of all time points combined.If the two independent reviewers disagreed, a third reviewer adjudicated.The site visits for source data verification took place over 7 months,March–September 2014. In total, 594 individual Clinical Research Associate visitdays were completed across all 63 recruiting sites. Source data verification wascompleted in full for 444 of 456 (97%) patients on all three arms. The remaining12 patients’ (3%) notes were irretrievable, but almost all could be partiallymonitored using annotations, laboratory reports and scan records. A total of3253 queries were raised, which is an average of 6.7 per patient. It took onaverage 1.2 days to complete the required checks for each of the 486 patientsrecruited to the trial. The contract research organization performing the sourcedata verification did not share data point changes with the Unit in a summarizedformat, though the Unit did record them for the quality control.Key data—7686data points were quality control checked and 36 errors were identified, which isan error rate of 0.47% and (b) Supporting data—25 of the total486 patients were checked; 59,261 data points were quality control checked and109 errors were identified, which is an error rate of 0.18%.Changes arising from the quality control were: (a) key data quality control, in 100% of patients, discovered 30errors related to SAE reporting (5% of 571 events), five to follow-up and one todeath (0.4% of 225). The death-related error was a data entry error where thedate of death was recorded as the date of form completion. The five errorsrelated to the follow-up form were a variety of data entry errors, mainly aone-digit error in the date last seen entry. The most common errors of the 30 inthe SAE forms were 10 errors in the action taken in regard to trial treatment inresponse to the SAE and eight related to the causal relationship of the trialtreatment to the SAE. The others related to expectedness (four), date of onset(three), SAE grade (three) and SAE name (two). No expedited reporting of seriousadverse reactions to sponsor or regulators was affected.The supporting data quality control, in a 5% sampleof patients, 109 errors were detected in 59,261 checked data points (0.18%). Thevast majority of these errors  were related to reporting of AEs.29% of the errors were misreported grade of severity. These errors areconcerning given the critical nature of safety reporting, though with up to 71grades to be entered on a single extensive AE form; over numerous visits atbaseline, chemotherapy and follow-up phases; and with 25 patients selected forreview this error rate is extremely low in totality.In terms of the It is not feasible to isolate and assess the efficacy impact of the source dataverification and the quality control separately; consequently, the results ofthese two processes will be presented together. Full statistics are provided inAfter source data verification and quality control, two previously unreportedprogression events were identified: one on each arm (A and C), resulting in a 1%increase in event rate in each arm. This actually represented the observation ofthree more progression events prior to the date of data cut-off, but oneprogression event was recorded in error pre-source data verification because thepatient had asked for no further follow-up on the trial. Overall, 34 changes toevent time were made, 11 in arm A and 23 in arm B (2:3 randomization ratio),with a median change of −7 days for arm A and −3 days for arm C.The log-rank test for equality of the curves provided very strong evidence of adifference between arm A and arm C both initially and after source dataverification/quality control, with a change only at the sixth decimal place.15 The Grambsch–Therneau test for non-proportionality p-value change didresult in an adjustment in interpretation, and so consequently the primarydescription of the difference became the hazard ratio over the restricted meansurvival time.For the hazard ratio, there was only a minor adjustment on one side of theconfidence interval. The restricted mean survival time estimated gain remainedat 3.1 months with small adjustments in the estimates of the two arms. In thestatistical analysis plan, it was stipulated that if there was evidence ofnon-proportionality, the restricted mean survival time would be used as theprimary point estimate of the treatment effect, and the hazard ratio if therewas no evidence, though both estimates would reported as a supportive evidence.Median progression-free survival times shortened slightly in arm C but remainedwith a 2.4 month gain in time to progression or death.The conclusion drawn for the primary outcome measure of progression-free survivaland in the primary comparison of arm A versus arm C was therefore unchanged fromthe initial presentation.In 1619 Again, all statistics arepresented in The number of patients included in the analysis set in the blinded independentcentral review was reduced by 4% in each arm in comparison with the localevaluation, due to only including those patients with at least one scan orradiological report provided for review. This meant the proportion of events wasreduced in absolute terms by 5% in arm A and by 3% in arm C. In arm A, onepatient (1%) had a newly identified progression and eight patients (7%) wereclassed as not having progressed—contrary to the primary analysis. The patternin arm C was rather similar in that two patients (1%) had progressions added and13 (8%) had theirs omitted. Overall, the concordance rate in ICON6 between thelocal evaluation and the blinded independent central review–based analyses was19%, which is comparable with other contemporary trials that have reported theirconcordance such as AGO-OVAR 16 (15%), GOG-0218 (23%), OCEANS (26%) and AURELIA(31%).Online Appendix). The test for non-proportionality p-value wasdifferent to the initial presentation and very similar to the post–source dataverification/quality control data, consequently the hazard ratio was used as theprimary estimate of the difference. The size of the hazard ratio benefit of armC was similar in both the local evaluation and blinded independent centralreview, but marginally stronger in the local evaluation. The restricted meansurvival time for the blinded independent central review–based analysis followedthe same pattern of a very slight reduction in the estimated gain.The strength of evidence for a progression-free survival difference between thetreatment arms using the log-rank test in the blinded independent central reviewanalysis decreased slightly, though still provided very strong evidence of adifference and should not be a surprise given the decrease in both populationsize and event rate. This difference in survival curves is presented graphicallyin 20 Grades within this system broadly correspond to the following: Grade 1“Mild”; Grade 2 “Moderate”; Grade 3 “Severe or medically significant but notimmediately life-threatening”; Grade 4 “Life-threatening consequences”; andGrade 5 “Death related to AE.”Toxicity on the trial was collected using Common Terminology Criteria for AdverseEvents (CTCAE) from the National Cancer Institute.During the conduct of ICON6, the National Cancer Institute revised the CTCAEscales, updating from version 3 to version 4. This occurred on 28 May 2009 bywhich time 71 of the eventual 486 patients had been recruited. The guidance forsites participating in the trial was that patients should continue with the sameversion of the form  with whichthey started on the trial to enable comparison with baseline grades given thechange in some key toxicities definitions. This meant 15% (71/486) should haveassessed patients using version 3, with the rest using version 4.4 This figure displays the highest grade of each toxicity experienced ontrial, separately for the two phases (during chemotherapy and on maintenance).As shown by the left-hand four plots, as expected, patients report very highlevels of all four toxicities during the chemotherapy phase. Comparing the“original” and “revised” bars, after source data verification/quality control,there were only very small uplifts in maximum grade reported in diarrhea, nauseaand fatigue—but some important differences within hypertension. This pattern ofa lack of difference for diarrhea, nausea and fatigue but increase inhypertension was also observed in the maintenance phase, as shown by theright-hand four plots, and so warrants further discussion. Within both thechemotherapy and maintenance phases, 12% of patients had their maximumhypertension grade altered and all of these changes were uplifts in grade. Themajority of the hypertension changes were due to blood pressure readings in thesource notes (70%) or the start of anti-hypertensive treatment (17%) which hadnot been reported on the forms for the trial. There was no evidence of asystematic bias by arm.The four key toxicities associated with vascular endothelial growth factortreatments and highlighted in the primary presentation are given in We had informal discussions with investigators around the reasons for bloodpressure readings not being recorded on forms. The conclusion being that thiswas a specific circumstance where the definition had changed and staff were morefamiliar with the older scale classification from version 3, substantially basedon need for changing therapeutic regimens, whereas the updated version 4mandated a change in grade based on firm numerical guidelines. Many clinicianswould have been comfortable with the older system and graded according to it.For example, a patient observed in clinic with a one-off blood pressure readingof systolic 140 or diastolic 90 previously would have been ungraded, but in therevised version would have been assigned grade 2 hypertension. The consequencebeing that some elevated blood pressure readings that met version 4 criteriawere not always recorded as hypertension AEs, but Clinical Research Associatescompleting the source data verification identified these as additional AEs. Thismay have been particularly so when the clinician considered the blood pressurereading was likely to be related to stress in clinic.In the original trial report, AEs were formally compared if they were experiencedby >5% of the trial population (described in the preceding paragraph), or ifthey were high grade  of any frequency.Within this high-grade AE reporting group, only two occurrences were altered.For one patient, their pneumonia was revised from grade 4 to grade 5 (arm A),and one grade 3 pancreatitis revised to grade 5 (arm C). Both had beenappropriately reported as fatal SAEs, and given the difficult nature ofassigning a definitive cause of death to a specific symptom, minor changes arenot surprising. There was a downgrading from grade 4 to grade 3 hypomagnesemiafor one arm C patient.We found that the three themes of retrospective data verification  made onlyimmaterial changes to the key outcome measures of the trial—and consequently itsinterpretation.21 and another which states that “discrepancies identified made no impact on themain conclusions of the study.”22 The quality control process did discover errors, in the keydata this almost met the 0.5% threshold we set that would signalconcern with trial conduct, but overall compared well to error rates in theliterature and again made no impact on the interpretation of the study.23 The blinded independent central review sensitivity analysis, on the contrary,did make a difference to individual assessments, as was expected given thecomplexity and partially subjective nature of declaring progression in cancerpatients, especially retrospectively. This sensitivity analysis supported theprimary, local evaluation, result in that the overall test of a difference and thesize of the estimate remained overwhelmingly positive. Consequently, the localevaluation conclusion that cediranib increases time to progression or death wasreinforced. The literature contains much discussion as to the limited added value ofblinded independent central review already and suggests that local evaluation“provides a reliable estimate of treatment effect” in most settings in the study ofcancer.25The two most time-consuming parts, the source data verification and quality control,had the least impact on the primary efficacy outcome measure. The impact of sourcedata verification was consistent with previously reported experiences, one of whichstates, “the true effectiveness value of source data verification […] is minimal (0.1%–0.4%)”26 It is our belief that these changes would not have altered the overalltoxicity assessment as the changes were not biased toward one arm, it was alreadyacknowledged that the toxic effects of vascular endothelial growth factor inhibitorscan be problematic, and prompt management guidelines were generally successful incontrolling further hypertension.As anticipated, there were some changes in the toxicity profile. For the most part,these were minor and made little or no difference to the standard toxicity summarystatistics and do not appear to have been systematically biased toward one treatmentarm. Some additional hypertension episodes were reported, though in discussion withtreating gynecological oncologists we feel that this is likely due to substantialdifferences in the method of grading hypertension between versions of the AE systemused. This meant that what many interpreted to be one-off, non-clinicallysignificant blood pressure readings were graded as a low-grade AE in the updated AEscale—for which a subset of investigators had not realized had been revised. Thissubstantial difference in definition of hypertension between versions is emphasizedby Akhtar et al. who, in study NCI 6981, observed the majority of patients (65%)increased by two grades in their retrospective regrading using version 4. Theyconcluded the impact of this change as “particularly important with vascularendothelial growth factor-targeted agents” such as cediranib.27 The EMA and FDA published their support for alternative approaches such ascentralized, risk-based monitoring in 2013 but the practice of extensive on-sitesource data verification was, and is still likely to be, commonplace incompany-sponsored trials.29A risk-based monitoring approach was used in the ICON6 trial, as is standard at theUnit given studies have demonstrated it to be non-inferior to extensive on-site monitoring.This retrospectively performed work took substantial amounts of time. Our crudeestimate is that it was the primary task for our trial team for 2 years, equivalentto 4.5 full-time staff members per year. External contractors were used for morefocused periods, but we estimate this to be equivalent to nine full-time staff peryear. It is likely that retrospectively conducting these processes would be moretime-consuming than if done prospectively.The conduct of this pragmatic, academic-led trial was sufficient given the robustnessof the results, shown by the results remaining largely unchanged followingretrospective verification. The burden of such comprehensive retrospective effortrequired to ensure the results of ICON6 were acceptable to regulators is difficultto justify.Click here for additional data file.Supplemental material, Appendix_rev3_clean for Impact of retrospective dataverification to prepare the ICON6 trial for use in a marketing authorizationapplication by Andrew Embleton-Thirsk, Elizabeth Deane, Stephen Townsend, LauraFarrelly, Babasola Popoola, Judith Parker, Gordon Rustin, Matthew Sydes, MaheshParmar, Jonathan Ledermann and Richard Kaplan in Clinical Trials


Smoking is a leading cause of numerous human disorders including pulmonary disease, cardiovascular disease, and cancer. Disease development is primarily caused by exposure to cigarette smoke constituents, many of which are known toxicants. Switching smokers to modified risk tobacco products (MRTPs) has been suggested as a potential means to reduce the risks of tobacco use, by reducing such exposure.™/THP1.0) or in-market comparator (iQOS/THS) tobacco heating product (THP). One hundred eighty Japanese smokers smoked combustible cigarettes during a 2-day baseline period, followed by randomization to either continue smoking cigarettes, switch to using mentholated or non-mentholated variants of glo™, switch to using a non-mentholated variant of iQOS, or quit nicotine and tobacco product use completely for 5 days. Baseline and post-randomization 24-h urine samples were collected for BoE analysis. Carbon monoxide was measured daily in exhaled breath (eCO).This randomized, controlled study investigated whether biomarkers of toxicant exposure (BoE) were reduced when smokers switched from smoking combustible cigarettes to using a novel (glop < .05) reduced by medians between 20.9% and 92.1% compared with baseline in all groups either using glo™ or iQOS or quitting tobacco use. Between-group comparisons revealed that the reductions in the glo™ groups were similar (p > .05) to quitting in many cases.On day 5 after switching, urinary BoE (excluding for nicotine) and eCO levels were significantly (™ or iQOS use for 5 days reduced exposure to smoke toxicants in a manner comparable to quitting tobacco use. THPs are reduced exposure tobacco products with the potential to be MRTPs.gloThis clinical study demonstrates that when smokers switched from smoking combustible cigarettes to using tobacco heating products their exposure to smoke toxicants was significantly decreased. In many cases, this was to the same extent as that seen when they quit smoking completely. This may indicate that these products have the potential to be reduced exposure and/or reduced risk tobacco products when used by smokers whose cigarette consumption is displaced completely.ISRCTN14301360 and UMIN000024988. Smoking-related disease risk is related to daily cigarette consumption and the number of years since smoking initiation and is principally due to exposure to a number of smoke toxicants transferred from the combustion of tobacco into cigarette smoke.7 many of which have been identified as potential contributors to the harmful effects of smoking. The 2001 report by the US Institute of Medicine (IoM) entitled Clearing the Smoke: the scientific basis for tobacco harm reduction4 proposed the development of potential reduced exposure products (PREPs) as a possible means by which to achieve tobacco harm reduction. Although reduced toxicant combustible cigarettes with the properties of a PREP have been described,9 significant changes in indicators of health were not observed in a long-term clinical study with such products.10 Since that time, other forms of tobacco products that heat instead of combust tobacco have been developed.12 We recently reported a pre-clinical assessment of the glo™ tobacco heating product (THP1.0),14 which electronically heats tobacco to a temperature of 240°C,12 and both its yields of machine-measured toxicants and environmental emissions are greatly reduced compared with those from conventional cigarettes.16 THP1.0 showed no or substantially reduced responses in mutagenic and cytotoxic endpoints relative to cigarettes in both in vitro toxicological and contemporary screening assays.17–19 Finally, a study with Japanese smokers showed that when they switch to glo™ over a 1-week period, they almost fully replaced their combustible cigarette consumption with glo™, and their combined daily cigarette and glo™ consumable consumption did not increase.20 The aim of this current study was to determine whether reductions in machine yields translated into a lowering of toxicant exposure, by measuring biomarkers of exposure (BoE) in a clinical confinement study in Japanese subjects who either continued smoking, used glo™/THP1.0 or an in-market comparator THP (iQOS/THS), or abstained completely from tobacco product use, for 5 days.Combustible cigarette smoke contains more than 6500 identified chemical constituents,21 Brief study details are described here.A full description of the study protocol has been published previously.This was a randomized, controlled, parallel group open-label clinical confinement study carried out at two sites in Fukuoka, Japan. The study was registered on both the ISRCTN (ISRCTN14301360) and the UMIN (UMIN000024988) registries. Favorable opinion for the study was given by the Hakata Clinic Institutional Review Board, Medical Co LTA, Fukuoka, Japan (reference number 1684CP). The study was conducted in compliance with the ethical principles of the Declaration of Helsinki, Good Clinical Practice  and Japanese laws, including those relating to the protection of subjects’ personal data.21 Main inclusion criteria were current smokers  who self-reported typically smoking daily at least 10 and a maximum of 30 commercially available cigarettes between the International Organization for Standardization (ISO) tar levels of 6–8 mg/cig; consecutive smoking history of at least 3 years; aged between 23 and 55 years inclusive.Healthy male or female smokers were enrolled in this study. During a screening visit, potential participants were assessed for their suitability based on inclusion/exclusion criteria which have been described in full previously.Main exclusion criteria were subjects who did not agree, or whose partners of childbearing potential did not agree, to use effective methods of contraception for the duration of the study from screening to discharge; female subjects who were pregnant or breastfeeding; subjects who had donated ≥400 mL of blood within 12 weeks  or 16 weeks  prior to admission; subjects who had an acute illness (eg upper respiratory tract infection) requiring treatment within 4 weeks prior to admission; subjects who had regularly used any nicotine or tobacco product other than factory-made filter cigarettes within 14 days of screening; subjects who were self-reported or observed at admission by the clinic staff as non-inhalers of cigarette smoke; and subjects who had any clinically relevant abnormal findings on physical examination, medical history, electrocardiography (ECG), lung function tests, or clinical laboratory panel. Subjects were also excluded if they were planning to quit smoking in the next 12 months. All subjects were informed that they were free to quit smoking and withdraw from the study at any time. Any subject who decided to quit smoking was directed to appropriate stop smoking services.™/THP1.0 with non-menthol Neostiks, a 7-mg/cig ISO tar combustible tobacco menthol cigarette, and glo™/THP1.0 with menthol Neostiks. The iQOS/THS product with non-menthol tobacco consumables was also studied as an in-market comparator product. Only those smokers who regularly smoke mentholated cigarettes were randomized to use mentholated products during the study. A further (abstinence) group refrained from using any tobacco or nicotine products after the switch at the end of the baseline period. Aerosol emissions for the THPs used in this study have been published previously.22 Smoke constituents for the comparator combustible cigarettes manufactured for this study are in All study cigarettes and THP devices/tobacco consumables were provided by the sponsor free of charge. A single study product was allocated to each group; these products were a 7-mg/cig ISO tar combustible tobacco non-menthol cigarette, glo23 Subjects who met all inclusion/exclusion criteria were entered into the study. On day –1, subjects entered the clinic, and 24-h urine collection periods began for 2 days, during which time all subjects smoked regular cigarettes. After this period and according to the randomization code, subjects remained smoking regular cigarettes, switched to using a THP, or refrained from using any tobacco products for 5 days. During this period, 24-h urine samples were collected for BoE analysis. On all study days, carbon monoxide in exhaled breath (eCO) was measured using a portable meter . Participant’s consumption of either cigarettes or THP tobacco consumables while in the clinic was limited to no more than 125% of their usual daily cigarette consumption.A study design schematic is shown in At the end of the 5-day exposure period, subjects (other than those in the abstinence group) remained in the clinic for a further day to undergo a nicotine pharmacokinetic assessment with their assigned product. Nicotine pharmacokinetic data from this assessment are not reported in this study.After the nicotine pharmacokinetic assessment was completed, participants were discharged from the clinic. All subjects were followed up by telephone 5–7 days after discharge to capture whether any subsequent adverse events (AEs) occurred.t test with 80% power for a decrease in biomarker levels of 40% or more compared with historical biomarker data available for a 7-mg/cig ISO tar conventional cigarette.10 A sample size of 30 was determined to be adequate based on the biomarker requiring the most pairs to power  and allowing for potential attrition. A sample size of 30 was also determined to be able to provide sufficient power for the secondary objective of between-group comparisons, based on a minimum of a 40% reduction in BoE.A sample size of 30 subjects per group was determined based on powering the primary objective of within-group comparisons of biomarker levels between baseline and end of study (days 6–7). The calculation was based on the number of pairs required to perform a paired Summary statistics and statistical analyses were performed for subjects included in the relevant analysis populations (safety/intent to treat/per protocol). Missing values were not imputed , and values below the analytical limit of detection (LOD) or lower limit of quantification (LLOQ) were replaced with half the value of the LOD or LLOQ, respectively. Data analysis was performed using SAS® Version 9.3.For biomarker data, the mean of the two values taken prior to first randomized product use (ie days –1 to 1 and days 1–2) was used as the baseline value. Mean change from baseline was the mean of all individual subjects’ change from baseline values. Each individual change from baseline was calculated by subtracting the individual subject’s baseline value from the value at the timepoint. Mean percent change from baseline was the mean of all individual subjects’ percent change from baseline values.The amount excreted for the urinary biomarkers over 24 h and the concentrations for CO in exhaled breath were summarized along with actual changes and percentage changes from baseline at each measurement.t test. Only subjects who had both baseline and days 6–7 data were included in the analysis. As a secondary objective, the baseline and days 6–7 values were also used to investigate comparisons between arms, using a mixed ANOVA with fixed terms for site, product use, day, and arm, and a random term for subject. Product use was defined as the number of cigarettes or THP consumables used per day recorded at baseline and days 6–7 by subject. If site was not significant (p > .05), it was not included in the model. The LS means difference from baseline was reported for each product separately. For each comparison, the difference in the changes from baseline between two products was also presented along with the 95% confidence intervals.The baseline and days 6–7 values were used to investigate the within-arm changes in biomarkers for each arm separately using a paired BoE to selected cigarette smoke constituents in 24-h urine collections were measured throughout the study from days –1 to 7. The study examined the following urinary BoE: total nicotine equivalents ; total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL); total N-nitrosonornicotine (NNN); 3-hydroxypropylmercapturic acid (3-HPMA); 3-hydroxy-1-methylpropylmercapturic acid (HMPMA); S-phenylmercapturic acid (S-PMA); monohydroxybutenyl-mercapturic acid (MHBMA); 2-cyanoethylmercapturic acid (CEMA); 4-aminobiphenyl (4-ABP); o-toluidine (o-Tol); 2-aminonaphthalene (2-AN); 1-hydroxypyrene (1-OHP); 2-hydroxyethylmercapturic acid (HEMA); N-acetyl-S-(2-carbamoylethyl)cysteine (AAMA); and N-acetyl-S-(2-hydroxy-2-carbamoylethyl)cysteine (GAMA).21Laboratory analyses were carried out at Celerion Laboratories  or ABF GmbH . Details on the bioanalytical methods have been published previously.Safety assessments included AEs, serious AEs (SAEs), vital signs, ECG, spirometry, clinical chemistry, hematology, urinalysis, physical examinations, and use of concomitant medications. AEs were recorded from the time of signing the informed consent form until the end of the follow-up period after discharge from the clinic. AEs, concomitant diseases, and medical/surgical history were coded using the Medical Dictionary for Regulatory Activities (MedDRA version 19.1).Overall 182 participants were enrolled into the study on day –1 and randomized to one of the six study groups. During the baseline period, two participants were withdrawn from the study. One was withdrawn on day 2 due to not meeting the eligibility criteria, and a further was withdrawn due to an AE of nasopharyngitis on day 1. Those withdrawn did not enter the exposure period and were replaced. Thus, 180 participants entered the exposure period and completed the study in accordance with the protocol.2 respectively).Demographic details of the study participants can be found in All subjects had a smoking history of at least 3 years and smoked between 10 and 30 cigarettes daily . SubjectFagerström Test for Cigarette Dependence scores were similar between study groups , rangingThe number of conventional cigarettes/THP consumables used during the baseline and exposure periods can be found in All 180 subjects had a valid assessment of BoE variables and completed the study. Four subjects had baseline values for o-toluidine that were above the upper limit of quantification and were erroneously high. Data on all days for these subjects were excluded from any summaries and statistical analysis. No data were log-transformed prior to the statistical analyses because the transformation did not markedly change the normality assumptions of the data, and the results of the analyses were still valid based on the raw data.™/THP1.0, the iQOS/THS THP, or to cessation were substantially and significantly decreased from baseline on days 6–7 (p < .05) with the exception of TNeq for the iQOS group (p = .09). Eight of the 16 BoE assessed were at a level below the analytical limit of quantification in at least one subject on days 6–7 . Similarly, changes from baseline for eCO in the non-menthol glo™ THP group, and total NNAL and 1-OHP in the menthol glo™ THP group, were not significantly different compared with the cessation group. Finally, although statistically significant decreases from baseline were observed on days 6–7 in both glo™ THP variant groups for TNeq, AAMA, and GAMA, the changes from baseline were significantly smaller than those observed in the cessation group (p < .05 in each case). The full secondary objectives statistical analysis can be found in For the majority of the BoE, the magnitudes of the reductions from baseline in the gloA summary of AEs occurring during the study can be found in Overall, 14 exposure period AEs were reported by 10 of the 180 subjects (5.6%). The numbers of exposure period AEs reported and the numbers of subjects reporting exposure period AEs were similar for all study arms. All exposure period AEs were of mild severity, with the exception of one severe AE, which was considered to be an SAE, and one moderate AE. The SAE was a pregnancy detected on discharge from the clinic despite negative pregnancy test results at screening and admission. None of the 14 exposure period AEs were considered to be related to the study product.™ THP group, and two subjects in the iQOS THP group. All of the presyncope AEs occurred on day 8 of the study during the nicotine pharmacokinetic assessment period, within 8 min of the start of their single-product use. There were 9 AEs reported by 6 of 180 subjects (3.3%) classified as investigations, including a positive urine pregnancy test, 3 AEs of increased alanine aminotransferase, 2 AEs of increased aspartate aminotransferase, 1 AE of glucose urine present, and 2 AEs of increased blood triglycerides. None of the investigation AEs were considered to be related to the study product. There were no clinically significant findings in the vital signs, ECG parameters, and lung function tests data.The most commonly reported exposure period AE was presyncope. This was reported by 5 of 180 subjects (2.8%): two subjects in the non-menthol cigarette group, one subject in the menthol glo24 Here, we report data from a randomized, controlled, dual-center open-label study in healthy Japanese smokers conducted to evaluate the effect of switching from a cigarette to menthol and non-menthol variants of the novel THP1.0 on BoE. In addition to the glo™ THP, biomarker levels were also investigated in participants who switched to using the in-market comparator THP iQOS/THS, or who completely abstained from any tobacco product use. Overall, use of the study products was safe and well tolerated. The majority of AEs reported were mild in severity, and none were considered related to the study products.Clinical studies examining exposure to toxicants are a key component of an overall assessment of novel tobacco and nicotine products for their impact on human health.25 and are of interest due to their potential link to smoking-related health risks. Substantial and statistically significant within-group reductions from baseline for all BoE were observed in subjects who switched from smoking conventional cigarettes to using either glo™ THP variant or to using the iQOS THP. For the majority of the biomarkers, the magnitudes of these reductions were not statistically significantly different from those observed in subjects who abstained from using any products after the baseline period. Furthermore, our results are generally consistent with the recent studies on other THP devices in Japan and Poland.27 While not definitive in terms of demonstrating risk reduction, these toxicant biomarker data are an important component when assessing the potential for changes in risk from tobacco product use.This study assessed 15 urinary BoE to cigarette smoke toxicants and one BoE in exhaled breath. These were selected based on the initial list of priority toxicants proposed by the World Health Organization Study Group on Tobacco Product Regulation™ THP group were not significantly different from those observed in the cessation group. In contrast, changes in NNAL were significantly different in the non-menthol glo™ group, and both menthol and non-menthol cigarette groups compared with the cessation group. The elimination half-life for NNAL is considerably longer (10–18 days) than for the other BoE assessed, and this can lead to carryover when subjects have switched to alternative nicotine products or abstain from tobacco product use.28 That NNAL levels were greater in the non-menthol glo™ group may be due to slightly higher product consumption than in the iQOS and menthol glo™ groups, and residual NNK in the THP tobacco consumable which, though minor compared with that in a combustible cigarette, still gives rise to NNK exposure. Further studies over a period of time longer than that of this 5-day switching study are required to examine the overall impact of THP use on NNK exposure, as well as to the other smoke constituents examined in this study.A secondary analysis of differences between the product use groups and cessation revealed that the urinary levels of the 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) biomarker NNAL, expressed as a percentage of the baseline level, in the menthol glo10 Interestingly, an uplift in consumption on the last day on which tobacco products were supplied to study participants was seen in all study groups, including the cessation group at the end of their baseline period. This lends further support to the idea that increases in consumption may be related to the provision of free tobacco products,29 with the participants increasing their consumption before this comes to an end.The 24-h product use counts were generally similar for all study arms at baseline ranging from mean values of 15.2 to 17.4 cig/24 h. During the exposure period and in all cigarette/THP groups, consumption increased minimally and, generally, by 1–2 cig/tobacco consumables per day. Despite this, participants’ consumption patterns both at baseline and during the exposure period were no greater than their self-reported pre-study consumption. Such escalating product use patterns are typical of confinement studies with tobacco products and have been seen in other studies previously.™ THP variant. These data suggest that the subjects were adjusting their usage of glo™ to achieve their desired levels of nicotine intake.The increase in non-combustible product consumption as the study progressed did not lead to an increased nicotine consumption, assessed by analyzing urinary excretion of TNeq, as the study progressed. Largely, TNeq levels remained stable or were reduced at the end of the exposure period, compared with those seen at baseline. Where decreases were seen, these were most apparent in the groups using either gloGSTT1-null genotype compared with other ethnic populations.30A number of subjects in all groups had urinary levels of MHBMA which were lower than the level of detection. This could potentially be due to issues with the sample collection and storage prior to assay, or alternatively, it could be due to genotype variations in the population resulting in lower or absent metabolism for this analyte. In support of the latter, there is evidence in the literature to suggest that urinary excretion of MHBMA is lower in Japanese populations with the While this confinement study design provides benefit in facilitating an examination of exposure changes when smokers switch to using THPs in a controlled environment and in the absence of confounding factors such as use of other products and not just the assigned product, it is not without limitation. By its very nature, a confinement study in a clinical environment is not able to determine whether such exposure changes would be seen in a more real-life setting. Thus, one limitation of this study is the lack of insight it gives into exposure reductions that may be observed in an ambulatory setting where other tobacco products are available for use. Secondary to that and further to the discussion on NNK exposure above, the length of this study precludes any conclusions being drawn on long-term changes in exposure to NNK when subjects switch from combusted to heated tobacco. Whilst subject demographics are reported, this study does not explore any potential relationship between changes in biomarker levels and other variables such as age and gender. This study also precludes drawing conclusions on reductions in exposure to smoke constituents other than those for which we examined BoE in this study. Finally, in the absence of conclusive data on potential dose–response relationships or threshold effects, any reductions in BoE cannot be extrapolated to confirm any reductions in health risk.™/THP1.0 showing reduced emissions and toxicological endpoints relative to cigarettes,14 glo™ has the potential to be a reduced exposure and/or reduced risk tobacco product when used by smokers whose cigarette consumption is displaced completely.The study demonstrated that switching from smoking to using THPs resulted in significant reductions in BoE for selected smoke constituents. For the majority of these biomarkers, the speed and magnitude of the reductions were comparable to those observed during smoking cessation. In this clinical study, the use of the study THPs was safe and well tolerated with a small number of AEs reported that were not attributed to study product use. Together with pre-clinical data on glohttp://www.ntr.oxfordjournals.org.Supplementary data can be found online at nty104_suppl_Supplementary_MaterialClick here for additional data file.The study was sponsored by British American Tobacco (Investments) Limited.NG, MMcE, ACE, OMC, GE, JMcA, JM, CL, and CJP are current employees of British American Tobacco (Investments) Limited (BAT). IMF was an employee of BAT for the duration of the study. NS was a consultant employed by BAT to provide consultancy services for this study. EB, SMcD, EH, AH, SH, LW, and JG are employees of Covance Clinical Research Unit Limited, a contract research organization to provide numerous services to the study.


The goals of the present study were to test whether (and which) basic numerical abilities can be improved with training and whether training effects transfer to improvement in children’s math achievement. The literature is mixed with evidence that does or does not substantiate the efficacy of training basic numerical ability. In the present study, we developed a child-friendly software named “123 Bakery” which includes four training modules; non-symbolic numerosity comparison, non-symbolic numerosity estimation, approximate arithmetic, and symbol-to-numerosity mapping. Fifty-six first graders were randomly assigned to either the training or control group. The training group participated in 6 weeks of training . All participants underwent pre- and post-training assessment of their basic numerical processing ability , overall math achievement and intelligence, 6 weeks apart. The acuity for numerosity discrimination  significantly improved after training, but this training effect did not transfer to improvement in symbolic, exact calculation, or any other math ability. We conclude that basic numerical cognition training leads to improvement in ANS acuity, but whether this effect transfers to symbolic math ability remains to be further tested. The ability to process numerosity information is essential for everyday life in both humans and animals . Approxi1  using dot arrays improved the training groups’ symbolic addition/subtraction abilities compared to the control group . In cont1  although1 . Szkudla1 . In thes1 .The goal of the present study was to investigate whether (and which) basic numerical abilities can be improved with training and to test whether the training effect transfers to improvement in overall math achievement. We developed a child-friendly computer based software named “123 Bakery” which included four modules for training basic numerical abilities . Exact, symbolic arithmetic practice during training was purposefully excluded in order to thoroughly test whether the effect of training on basic numerical cognition truly transfers to exact, symbolic math ability without explicit practice in this domain. Our software was designed to include several training modules within each session, as in typical educational interventions . Trainina priori hypothesis in favor of the idea that basic math abilities can be improved with training and that such training effects will be transferred to improvement in math achievement . By using sufficiently long duration of training and wide range of magnitudes , we did not make type II error due to insufficient duration/range of training or contamination by extraneous variables.Given inconsistencies in the literature, we did not have an Supplementary Materials for further details.) Thus, data from forty-six children were included in the analysis . Participants were recruited by advertisement. All participants and their parents provided written informed consent before participation. The IRB committee of Chung-Ang University approved all protocols of the study (IRB-2013-55). Participants were randomly assigned to either the training or control group. Participants received monetary compensation after completion of the experiment.Fifty-six 1st graders participated in the study. Data from 10 children who did not complete the experiment or whose performance  was lower than 2 SDs below the mean were excluded. (See n = 22) or control (n = 24) group. Pre-training assessments  were administered to all participants. Only the training group participated in 30 training sessions over 6 weeks using a computerized software (“123 Bakery”). After 6 weeks had passed since the administration of the pre-training assessment, all participants were administered post-training assessment. The pre- and post-training assessments of basic numerical abilities were conducted with four tasks corresponding to each training module using alternate visual formats in order to minimize practice or test–retest effects at the visuomotor level .Participants were randomly assigned to either the training . Task difficulty increased as subjects mastered each Level by accomplishing a certain degree of performance accuracy .We developed a computerized program named “123 Bakery” which composed of four training modules. The four training modules included (1) numerosity comparison (“Gathering Ingredients”), (2) non-symbolic numberline estimation (“Guess How Many?”), (3) Approximate Addition & Subtraction (“Cake Decoration”), and (4) Symbol-to-Numerosity Mapping (“Selling Cakes”). (Each training module is explained in the next section.) Each module was 6 minutes long. Feedback on the correctness of the response was provided after each trial. The cumulative total score (within each session) was updated real-time and was always shown on the top right-hand side of the screen  during numerosity processing, we made convex hull equivalent for all dot arrays and divided trials into two control conditions (area vs. size controlled conditions) . First, Figure 2A). Task difficulty increased as the set size became larger (range = 6–200) and as the ratio of magnitudes approached 1 (range = 2:3–9:10). Audiovisual feedback on the correctness of the response was provided after each trial.Two arrays (of berries or nuts) appeared side by side for 1,000 ms. Subjects were instructed to choose the more numerous array . If the estimate was within the “accurate zone” (see Supplementary Table S2 for details), positive feedback was given. Task difficulty varied by the numerosity of the stimulus, the maximum value (end point) of the numberline, and the relative width  of the accurate zone.Subjects were presented with an array  for 1,000 ms at the center of the screen. Subjects were asked to click on a location on the numberline which corresponds to the estimated numerosity of the elements of the array . Audiovisual feedback on the correctness of the response was provided after each trial.Subjects were presented with two arrays  for 1,000 ms and were asked to perform approximate addition or subtraction. Then, two arrays were additionally shown as options to choose from. Subjects were asked to respond by choosing one of the two options which seemed closer to their approximate answer within 6 s . Task difficulty increased as the ratio of numerosities approached 1 and as the price of the cake increased. Audiovisual feedback on the correctness of the response was provided after each trial.Subjects were asked to choose which animal character (the customer) possessed the correct number of nuts which corresponded to the price of the cake   had the same structure as the four training modules except that the array consisted of black dots on a white background. Each task is explained in the following sections.Figure 3). Subjects pressed the #3 key for the array on the left and #8 key for the array on the right. The left–right location of the correct answer was counterbalanced. The ratio of numerosities included 1:2, 3:4, 5:6, 6:7, 7:, and 8:9. The entire stimulus list is shown in Supplementary Table S5. There was a total of 120 trials.Subjects were presented with a pair of dot arrays  and were asked to choose the array with the greater number of dots . The trials were divided into two blocks based on the value of the end point of the numberline (100 or 200). The stimuli included 5, 18, 32, 55, 73, and 98 for block 1 and 5, 18, 42, 78, 111, 133, 147, 172, and 187 for block 2. The target stimulus appeared for 1,000 ms.The numberline estimation task was conducted using both symbolic  and non-symbolic magnitudes  . SmallerEq. 1. Calculation of PAEFigure 5). Next, another dot array was either added to or removed from the gray box. Finally, the subjects chose one of two new dot arrays whose numerosity seemed closer to the perceived total number of dots in the gray box. They responded by pressing the #3 key to choose the array on the left and #8 key for the array on the right. Task difficulty was manipulated by the ratio of the set sizes of the two arrays  presented as a pair on each trial. Addition and subtraction were performed on arrays with numerosities ranging from 6–51. The numerosity of arrays presented as options ranged from 16–91. Including 5 practice trials, a total of 35 trials were administered.The procedure of the task was similar to the Approximate Arithmetic condition used in Figure 1B). The ratio between the magnitude of the stimuli varied from 1:1.75 to 4:5 . The set size of the stimuli varied from 6 to 100 . The left–right position of the correct answer was counterbalanced. A total of 144 trials were administered. The order of trials from each ratio/condition was randomly intermixed.Subjects were asked to choose one of two arrays presented for 1000 ms whose numerosity matched the Arabic number presented at the center of the screen   was usedSubjects solved 64 problems of addition and subtraction without paper and pencil on a computer. Three ranges of numbers were used . Participants were instructed to type the answer using the number keys on the keyboard. There was no time limit. (Accuracy rather than RT of problem solving was emphasized). Thus, accuracy rather than RT was the main dependent variable of interest.Children’s fluid intelligence was measured with an abbreviated version of the Raven’s APM test . This sct-tests revealed no difference in age  and gender  between groups. In addition, our groups did not differ on pre- and post-training assessments of math achievement or fluid intelligence .The training and control group were matched on age and gender. Independent samples Table 1. The training group’s performance at the end of each session for each module of “123 Bakery” are shown in Figure 6. The final Level reached at the end of training for each module of “123 Bakery” and the overall average of the 30 mean performance scores (accuracy and RT) from each session are provided in Supplementary Table S6. In order to test for training effects, a 2×2 mixed repeated measures ANOVA was conducted on basic number processing performance  with time  as the within-subject factor and group  as the between-subject factor (Table 2). A significant two-way interaction would indicate the presence of a training effect that is selective for the training group compared to the control group. The two-way interaction between time and group was significant only for numerosity comparison accuracy . . Given the significant two-way interaction effect, post hoc tests of the simple main effects of group at each time  were conducted for numerosity comparison accuracy. A significant training effect should be manifested as higher post-training (but not pre-training) performance of the training group compared to the control group. There was no difference in numerosity comparison accuracy between the training and control group at pre-training, but the training group had significantly higher numerosity comparison accuracy at post-training . In other words, training with the “Gathering Ingredients” module improved the training group’s numerosity comparison accuracy.Descriptive statistics of performance from pre- and post- training assessments of basic number processing abilities are provided in Table 3. The results of independent samples t-tests at each time  for each assessment score are also shown in Table 3. In order to investigate whether the effect of training transfers to improvement on math achievement, a mixed repeated measures ANOVA was conducted on all mathematical achievement scores (KNISE-BAAT and computerized arithmetic) with time  as the within-subject factor and group  as the between-subject factor (Table 4). There were no significant interaction effects on either KNISE BAAT or computerized arithmetic scores .Descriptive statistics of performance from pre- and post-training assessments of math achievement are provided in The present study examined whether or which basic numerical processing ability can be improved with training and whether this training effect can be transferred to improvement in different domains of mathematical achievement. We developed a child-friendly training program called “123 Bakery” which included four training modules . The dot arrays used as stimuli representing non-symbolic magnitude were controlled so that the influence of non-numerical visual properties was minimized. Exact, symbolic calculation was purposefully excluded from training in order to examine whether training on basic numerical ability improves exact, symbolic calculation while ruling out direct practice or test–retest effects. All participants were assessed on their basic numerical ability twice, 6 weeks apart. The training group participated in 6 weeks of training immediately after the first assessment. The second assessment took place immediately after the training session ended. Compared to the control group, the numerosity comparison accuracy of the training group improved significantly more at post-training assessment. This result is consistent with previous studies reporting improvement of ANS acuity after training . HoweverSeveral aspects of the present study are worth noting. Compared to previous studies, the period of training was much longer and the range of magnitudes used for both training and assessment was much larger. Furthermore, non-numerical visual magnitudes of stimuli were controlled for during both training and assessment. In addition, different visual interfaces of tasks were used between training vs. assessment to prevent direct practice effects. Our training was conducted in the child’s home to improve ecological validity to real-world, educational applications. Based on the analysis of our data, we could not find any evidence in support of training effects that transfer to improvement in any domain of math achievement. The only effect of training observed was improvement in the accuracy of numerosity comparison.The results of the present study are in contrast with those reported by some training studies conducted with young children . In our Inconsistencies across studies may also be due to differences in the contents of the training across studies. First of all, transfer effects to symbolic math reported from training studies which included symbolic arithmetic practice  may reflect direct practice effects because the training program itself included symbolic arithmetic practice . Second,common mental operations . This hypothesis was based on the observation that training effects from both numerosity comparison and approximate addition transferred to improvement in symbolic addition in children  for the control group. We acknowledge this as a limitation of the present study. If there had been a transfer effect of training on math achievement selectively for the training group, it would have been hard to eliminate the possibility of a placebo (or Hawthorne) effect. However, given the absence of a transfer effect, the lack of a control training program can be thought to be less of a problem in the case of the present study. Furthermore, The absence of transfer effect in our home-based training study raises the question of whether transfer effects observed within a lab-based setting will generalize to real-world or actual educational applications. Taken together, the results of the present study reveal that (1) only certain kinds of basic numerical ability  of young children can be improved with training and (2) improvement on ANS acuity does not seem transfer to improvement in math achievement, despite extensive training for 6 weeks, across large ranges of magnitudes.The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.NK contributed to designing the pre- and post-training assessments, improving the design of the training program, data collection, and analysis. SJ contributed to designing the training paradigm, data collection, and analysis. SC is the principle investigator who contributed to all aspects of the study from acquiring funding, designing the study, and monitoring all aspects of data collection and analysis. All authors contributed to writing the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The patient's pattern identification has been used for personalized medicine in traditional Korean medicine (TKM) and aims for patient-specific therapy by Korean medical doctors. The pattern identification in this trial will be diagnosed from body constitution questionnaire (BCQ) with a more objective diagnosis of it but this method still needs a more concrete scientific basis. Glycoproteins are well-known to be associated with diseases  so glycoproteomics can be applied to differentiate pattern identification types of lung cancer patients. Thus, for the first time proteomics approach will be applied to the pattern identification by comparing BCQ assessment in order to establish a scientific basis with clinical proteomics for precision medicine.This observational trial will at first diagnose the pattern identification types of lung cancer patients with BCQ assessment and then elucidate their relationships with proteomics. Blood samples will be collected before surgery along with clinical information of participants. The patients’ pattern identification in TKM will be diagnosed from BCQ assessment. Then, lung cancer patients will be divided and pooled into 3 lung cancer entire (LCE) groups according to their pattern identification types . Three lung cancer representative (LCR) groups will be selected and pooled from each LCE group by selecting those with the same control factors. The 3 LCE groups and the 3 LCR groups from lung cancer patients will be independently analyzed through the glycoproteomics approach based on the patients’ pattern identification. Glycoproteins from the 6 groups will be identified through proteomics approach and then categorized for analysis.This study intends to diagnose pattern identification of patients in TKM with BCQ assessment and proteomics approach. The identification of the glycoproteins in each group will lead to the scientific foundation of personalized medicine in TKM according to patients’ pattern identification for lung cancer therapy. We intend to(1) diagnose the pattern identification types of lung cancer patients with BCQ under the framework of TKM;(2) evaluate BCQ assessment with glycoproteomics approach for precision medicine.ClinicalTrials.gov NCT03384680. Registered 27 December 2017. Retrospectively registered. This will eventually improve the quality of life of cancer patients. The treatments based on traditional Korean medicine (TKM), a branch of complementary and alternative medicines, have been successfully applied to cancer patients to control the side effects of antineoplastic medicine in combined Oriental and Western medicine (COWM).–4 Compared to Western medicine, TKM is fundamentally different in the treatment process for cancer patients; there is an important step of “pattern identification” for patient-specific diagnosis and medication. Pattern identification is a practice in TKM where the treatment is determined after the body constitution of the patients and their symptoms are holistically examined. These treatments are generally determined by the patients’ pattern identification as well as the diagnosed disease and are thus personalized medicine. Precision medicine, also known as personalized medicine, is an emerging treatment strategy targeted to the needs of individual patients on the basis of genetic, biomarker, phenotypic, or psychosocial characteristics that distinguish a given patient from other patients with similar clinical presentations.–7 Therefore, Asia including Korea has already been using precision medicine according to patients’ pattern identification type traditionally, and TKM determined by pattern identification is a precision medicine by itself.Chemotherapy as a conventional treatment aims for reduction, suppression, and removal of cancer, but cancer patients commonly suffer from severe side effects from it. Furthermore, in cancer patients, tumor-induced symptoms and chemotherapy-induced symptoms are often manifested in combination. But since clinical trials using pattern identification are gradually increasing as the importance of precision medicine is being recognized, there has been studies using pattern identification in clinical trials for cancer patients. Also, traditionally diagnoses of pattern identification relied on patients’ subjective descriptions and doctors’ subjective judgments–13, many studies on questionnaires such as body constitution questionnaire (BCQ) have been developed.–17 This BCQ has been utilized to the clinical studies including breast cancer, liver cancer, diabetes–22, schizophrenia, and menopausal symptoms, as well as healthy control groups. BCQ enables us to assess patients’ pattern identification types according to their body constitutions using 19 to 23 simple-to-answer (survey) questions. This pattern identification tool can be more objective compared to the examination by individual TKM doctors.–28 However, BCQ still requires a proven scientific basis for determining pattern identification of patients as well as wide acceptance from the TKM community. This study intends to find a scientific standard on the pattern identification of lung cancer patients in the framework of TKM.Pattern identification of each patient has not been widely applied to clinical trials in which objective criteria are important. For males, in particular, lung cancer also leads all other cancers in both the number of new cases and the number of deaths. It is notable that for both genders, the number of deaths from lung cancer is more than twice that of colorectum cancer, the second-tier in the number of deaths. In Korea, lung cancer is also the leading cause of death for both genders among the 24 types of cancers according to recent cancer statistics reports jointly published by Ministry for Health and Welfare and National Cancer Center of South Korea in 2018. These cancer statistics illustrate that lung cancer causes the largest number of deaths worldwide and indicate the importance of lung cancer therapy for cancer patients worldwide.Lung cancer was reported to be ranked first in both the number of new cases and the number of deaths for both genders among 36 types of cancers (excluding non-melanoma skin cancer) in 2018 which was estimated by The International Agency for Research on Cancer (IARC) to inform about cancer control and cancer research from 186 countries.–33 Since glycans in glycoproteins are significantly altered in cancer, they may serve as a tool for judging chemotherapy efficacy. Recent studies have reported changes in α-1-antitrypsin (A1AT) glycosylation in lung cancer serum, tissues, and cell lines.–37 According to this study, a lectin microarray was used to detect glycosylation changes in serum A1AT from patients with lung adenocarcinoma (ADC), squamous cell lung cancer, small-cell lung cancer (SCLC), and benign pulmonary diseases. Differentially expressed glycosylated patterns of A1AT were identified by lectin arrays and were confirmed by lectin-based enzyme-linked immunosorbent assay (ELISA). This observational study is supported by these studies and suggests that the glycoproteomics approach may identify glycosylation differences among the 3 different pattern identification types in lung cancer plasma. Lung cancer patients will be pooled based on their pattern identification types diagnosed with BCQ assessment and then the glycoproteomics approach will be applied to each pooled pattern identification plasma.Cancer-associated glycoproteins have been reported to be shed into blood and lymph.22.1This observational trial will at first diagnose the pattern identification types of lung cancer patients with BCQ and then elucidate their relationships with proteomics. The study will be carried out in 2 groups; a lung cancer entire (LCE) group and a lung cancer representative (LCR) group, and these 2 groups will be described in further sections in detail. Figure 2.22.2.11.Diagnosis of each pattern identification of Korean lung cancer patients with BCQs.2.Verification of the correlation of BCQ and blood on each patients’ pattern identification type through glycoproteomics.3.Protein identification and categorization by patients’ pattern identification for patient-specific diagnosis and medication in TKM.2.2.2(1)Diagnosis of the pattern identification of Korean patients with scientific basis.(2)Biomarker discovery on each pattern identification type of lung cancer patients within a large population.(3)Development and commercialization of precision medicine on each pattern identification type.(4)Tracking the efficacy of patient-specific treatments according to each pattern identification type with clinical proteomics in the follow-ups.2.3Recruitment of participants began in September 2015, and the participants are lung cancer patients from Korea University Guro Hospital . All patients are Korean males and females over the age of 18 years. Participants are recruited by a lung cancer doctor in the University Guro Hospital  if they fulfill the eligibility criteria recommended by the investigators.2.4The inclusion and exclusion criteria of this trial are described in Table 2.5 Yin deficiency (Yin-Xu) indicates a decrease in many physical aspects of human body including blood, interstitial fluid, and other bodily fluids and may result in thirsty, flush, dry stool, and decrease in urine output. Stasis is the inadequate transport of the physical aspects of the human body by energy due to the imbalance between Yin and Yang. Blood stasis and phlegm result from Stasis. Symptoms including joint pain, chest tightness or pain, lumps, and cough may arise. The BCQ(+), BCQ(−), and BCQ(s) questionnaires are developed in order to differentiate among Yang-Xu, Yin-Xu, and Stasis with a more objective method.–28,39–41Pattern identification of a patient, expressed as either Yang or Yin, determines the patient's sensitivity for pathology. Yang deficiency (Yang-Xu) indicates a decrease of energy level in the physiological function of body and may cause fatigue, shortness of breath, chills, loose or watery stool, and polyuria.2.5.1 BCQ(−) is composed of another set of 19 questions with the same 5-point Likert scales, with the cut-off score of 29.5 points for Yin-Xu. BCQ(s) consists of 23 questions with the same Likert scale and cut-off score of 26.5 points for Stasis. A patient is diagnosed as Yang-Xu, Yin-Xu, and/or Stasis if his/her total score exceeds the corresponding cut-off score for each respective questionnaire. Therefore, patients will be categorized into 8 body constitutions of Yang-Xu, Yin-Xu&Yang-Xu, Yang-Xu & Stasis, Yin-Xu, Yin-Xu & Yang-Xu & Stasis, Yin-Xu & Stasis, Stasis, and Gentleness based on their BCQ scores.,25BCQ(+) is a questionnaire that is comprised of 19 questions with 1-to-5 rating scales, making the range of total score to be from 19 to 95 points with the cut-off score of 30.5 points for Yang-Xu.2.5.2–28 Patients who belong to none of the 3 body constitutions  will be classified into the Gentleness group,25. Therefore, the 8 body constitution types will be regrouped into 3 pattern identification types, Xu, Stasis, and Gentleness.Yang-Xu or Yin-Xu constitution is shaped by the persisting decrease of Yang or Yin, so patients who correspond to either Yang-Xu or Yin-Xu  will be classified into Xu (Deficiency) group. On the other hand, patients that are diagnosed as Stasis through BCQ(s) will be included in Stasis group since “Stasis” constitution is formed by the persistent disruption of the dynamic balance between Yin and Yang.2.62.6.1Lung cancer patients will be interviewed face-to-face for 19 categories of clinical information, including sex, age, race, body weight, body height, disease history , surgical history, family history, medication history, smoking, alcohol, and cancer diagnostic information .2.6.2Lung cancer patients will be randomly recruited without any prior categorization of their body constitutions. A disease of a patient with a certain type of pattern identification may be considered as arising from the patient's body constitution. Thus, it is important to holistically analyze all the lung cancer samples according to their pattern identification types.2.6.3All the lung cancer patients will be divided into 3 LCE groups according to their pattern identification types . The patients who will be assessed as Xu will belong to lung cancer entire Xu (LCEX) group. Likewise, the patients who will be assessed as Stasis will be included to lung cancer entire Stasis (LCES) group, while patients to be assessed as Gentleness will belong to lung cancer entire Gentleness (LCEG) group.2.72.7.1Sampling is particularly crucial when heterogeneous materials are analyzed. It is critical that the analysis aims are clearly declared and that an appropriate sampling procedure is adopted. In some situations, a sampling strategy needs to be devised in order to optimize the value of the analytical information collected. A representative sample is what truly reflects the composition of the material to be analyzed within the context of a defined analytical problem.2.7.2Glycoproteins in blood can vary qualitatively and quantitatively by numerous variables such as sex, age, and medical history. The glycoproteins must be qualitatively and quantitatively analyzed based on the pattern identification of the lung cancer patients. We hypothesize that each pattern identification of TKM as well as other variables such as sex, age, medical history, and etc. affects glycosylations on plasma proteins. Therefore, all the other variables other than pattern identification must be strictly controlled.Since it is impossible to control all of the 19 variables of clinical information, we need to select as many variables as possible that are within our control. For example, smoking can be selected as the control factor that is closely related to lung cancer while sex ratio and average age can be considered as basic control factors for qualitative and quantitative analysis of glycoproteins. Both TNM stage and cancer subtype can be selected as control factors. Disease histories can be selected as control factors that can affect glycosylation in cancer plasma. Patients with no prior history of cancers other than lung cancer will be selected because other cancers may affect the aberration in the glycan moieties of glycoproteins in the plasma. Cancer histories from direct family can be considered as a genetic factor.2.7.3The LCR groups will be generated from each LCE group by applying the selected control factors to lung cancer patient samples. The selected samples from LCEX group will be included in the lung cancer representative Xu (LCRX) group. Likewise, the selected samples from LCES group will be assigned to the lung cancer representative Stasis (LCRS) group while samples from LCEG group will be included in the lung cancer representative Gentleness (LCRG) group. The representative samples must be selected to have the same numbers of samples in each control factor for all pattern identification groups. It is also crucial to select a sufficient number of samples in order to reflect each pattern identification group. The number of patients with each control factor will be kept constant in each representative group.2.7.4Comparison of the identified glycoproteins between the LCE groups and the LCR groups with the same pattern identification type may reveal whether each LCR group truly represents each LCE group. This will be used to validate the unique glycoproteins from each pattern identification type of lung cancer patients under the framework of TKM.2.8As a preliminary trial for exploring proteomics approach based on pattern identification, we intend to enroll 100 participants.2.8.1At least 10 patients will be assigned to each group.2.8.2All LCR groups must have the same number of samples. The number of samples in these 3 LCR groups will be set by setting all the control factors other than pattern identification constant.2.9Ten milliliters of blood will be withdrawn from each lung cancer patient before surgery and mixed on a blood mixer at room temperature. The mixed blood will be centrifuged for plasma separation from blood cells and the supernatant plasma will be transferred to a tube and stored in −80°C deep freezer until filtration. All the plasma samples will be filtered and pooled together according to each LCE group and LCR group. The 6 pooled samples will be stored in a −80°C deep freezer until affinity selection.2.10Glycoprotein capturing lectin column will be self-packed and connected to high performance liquid chromatography (HPLC) system for lectin affinity chromatography (LAC). Pooled human plasma from lung cancer patients will be loaded directly onto the column with mobile phase. The detailed affinity chromatographic method will follow the method section of the reference paper.2.11 The PNGase F-treated peptide mixtures will be stored at −80°C until analyses.The selected proteins will be digested with sequencing grade trypsin for protein digestion and then with PNGase F for deglycosylation of glycoproteins. The detailed proteomics method will follow the method section of the reference paper.2.12The PNGase F-treated peptide mixtures from the 6 groups  will be analyzed with a nano liquid chromatography-tandem mass spectrometry (nLC-MS/MS). Each sample will be run more than twice under the identical conditions. The operational instruments and detailed methods will be in the method section of the reference paper.2.13After at least 2 MS/MS data are obtained from each sample, protein identification will be performed with 2 complementary database search programs. Both Proteome Discoverer 1.4  and ProteinPilot 5.0  will be used to identify proteins from MS and MS/MS spectra. Each software program has its own unique analysis algorithm. Thus, it will be meaningful to compare the results from the 2 programs because it will reinforce the confidence of the identified proteins. At least 4 data files with identified proteins will be produced from each sample. Each data file will be individually sorted and filtered under the following conditions:(1)dynamic modification option: deamidated (N-glycosylation)(2)peptide confidence levels: the peptide is significant only if (a) confidence levels are over 95%, or (b) confidence levels are below 95% in 2 runs but show significant MS/MS spectra.(3)proteins inclusion and exclusion: for Proteome Discoverer software, only the proteins with protein scores of 6.0 or higher will be included; for ProteinPilot software, only the proteins with the unused values of 2.0 or higher will be included. The rest of the identified proteins will be excluded from the results.Starting with the significant data from the 2 software programs, only the peptides/proteins with N-glycosylation sites will be selected and used for the parent protein identification. These glycoproteins will be sorted and compared within each group . Then these proteins will be sorted into those that are identified in all LCE groups, all LCR groups, and only certain group(s). The resulting 6 N-glycoprotein lists will be used for the following 5 comparative analyses:(1)the glycoprotein comparison sets from the first and second MS/MS runs for the confirmation of reproducibility(2)the glycoprotein comparison sets from the 2 protein search engines to increase the confidence level of identified proteins(3)the glycoprotein comparison sets between LCE groups and LCR groups to check the representativeness(4)the unique and intersection glycoproteins set by comparison of LCE groups  based on their pattern identifications assessed from BCQs of the lung cancer patients(5)the unique and intersection glycoproteins set by comparison of LCR groups  based on their pattern identifications assessed from BCQs of the lung cancer patients.The overall data processing and analysis procedures are described in Figure 2.14The study was approved by the Institutional Review Board (IRB) of Kyung Hee University  and Korea University Guro Hospital . The reference numbers are KUGH15010–002 for Korea University Guro Hospital and KHSIRB-15–005(RA) for Kyung Hee University. Prior to undertaking any study-related procedures, written informed consent will be collected from all participants.2.15Trial monitoring is performed by the Institute of Safety, Efficacy and Effectiveness Evaluation for Korean Medicine of the Kyung Hee University, Korea. A qualified investigator monitors this study. The investigator ensures that all the procedures are carried out, recorded, and reported in accordance with the standard operating procedures and all applicable regulatory requirements. Because this is a non-interventional study, it represents no risk or benefit for the patient.A data monitoring committee (DMC) is not needed in this study since this is an observational trial and there are no intervention or security risks for patients.3–40 and Hong Kong. This study is also the first to apply BCQ assessment to lung cancer patients. Furthermore, this is the first to correlate BCQ and patients’ blood through glycoproteomics. After diagnosis of pattern identification type with BCQ, glycoproteomics approach will be introduced to all the plasma in order to establish scientific and biomedical criteria on BCQ for the first time. Two sets of patients’ plasma will be explored from each pattern identification type of TKM; a holistic evaluation (LCE groups) and a scientific validation of the representativeness (LCR groups). It is regarded that the diseases of a patient with specific pattern identification arise from the corresponding pattern identification. Thus, it is important to holistically analyze the entire lung cancer patients according to their pattern identification types. On the other hand, by carefully selecting appropriate control factors, all the control factors other than the pattern identification are prevented from interfering with the change in glycoproteins in their blood. This change may vary depending on diverse variables such as sex, age, and medical history.This is the first study in Korea to diagnose pattern identification with BCQ assessment which was proven to obtain validity and reliability in TaiwanThe patient-optimized TKM for lung cancer can be applied to cancer therapy for future clinical trials and treatments by presenting scientifically valid criteria on patient's pattern identification from this trial. The identified plasma proteins from each pattern identification type will be categorized as pattern identification indicators (biomarkers) for precision medicine. In the long run, these proteins can also be utilized as lung cancer biomarkers aiming for development of in vitro lung cancer diagnostic kits based on pattern identification of lung cancer patients.WC has written this manuscript, is in charge of proteomics, and is one of the general supervisors for this research. JHK contributed to the design of this study, collected the specimens (coordinated to acquire/collect the specimens), and participated in the drafting the manuscript. MJ and JL contributed to the conception and design of proteomics approach and made a substantial contribution to the drafting of the manuscript. CC and SP contributed to the design of this study, to analyze the BCQ questionnaire and classification, and helped to draft the manuscript. MK and HS contributed to the collection of the specimens. SGK contributed to the funding, is one of the general supervisors for this research and participated in both the study design and critical revision of the manuscript. All authors read and approved the final manuscript to be submitted.Conceptualization: Wonryeon Cho, Ji Hye Kim, Chunhoo Cheon, Sunju Park.Funding acquisition: Seong-Gyu Ko.Investigation: Chunhoo Cheon, Sunju Park.Methodology: Miseon Jeong, Jinwook Lee.Project administration: Wonryeon Cho, Seong-Gyu Ko.Resources: Ji Hye Kim, Myeong-Sun Kim, Hyoungwoo Son.Supervision: Wonryeon Cho, Seong-Gyu Ko.Writing – original draft: Wonryeon Cho, Miseon Jeong, Jinwook Lee, Chunhoo Cheon.Writing – review & editing: Wonryeon Cho, Ji Hye Kim.Wonryeon Cho orcid: 0000-0002-9953-6176.