Salmonella enterica serotype Typhi (S Typhi) and Salmonella enterica serotype Paratyphi (S Paratyphi), which are the causative agents of enteric fever. We aimed to determine the burden of enteric fever in three urban sites in Africa and Asia.Enteric fever is a serious public health concern in many low-income and middle-income countries. Numerous data gaps exist concerning the epidemiology of S Typhi and S Paratyphi infection, and calculated adjusted incidence and seroincidence of S Typhi blood-culture-confirmed infection.In this multicentre population-based study, we did a demographic census at three urban sites in Africa  and Asia  between June 1, 2016, and Sept 25, 2018. Households were selected randomly from the demographic census. Participants from within the geographical census area presenting to study health-care facilities were approached for recruitment if they had a history of fever for 72 h or more (later changed to >48 h) or temperature of 38·0°C or higher. Facility-based passive surveillance was done between Nov 11, 2016, and Dec 31, 2018, with blood-culture collection for febrile illness. We also did a community-based serological survey to obtain data on Vi-antibody defined infections. We calculated crude incidence for blood-culture-confirmed S Typhi and 108 S Paratyphi A isolates were collected from the blood of 12 082 febrile patients. Multidrug resistance was observed in 44% S Typhi isolates and fluoroquinolone resistance in 61% of S Typhi isolates. In Blantyre, the overall crude incidence of blood-culture confirmed S Typhi was 58 cases per 100 000 person-years of observation (95% CI 48–70); the adjusted incidence was 444 cases per 100 000 person-years of observation . The corresponding rates were 74 (95% CI 62–87) and 1062 (95% CrI 683–1839) in Kathmandu, and 161 (95% CI 145–179) and 1135 (95% CrI 898–1480) in Dhaka. S Paratyphi was not found in Blantyre; overall crude incidence of blood-culture-confirmed S Paratyphi A infection was 6 cases per 100 000 person-years of observation (95% CI 3–11) in Kathmandu and 42 (95% CI 34–52) in Dhaka. Seroconversion rates for S Typhi infection per 100 000 person-years estimated from anti-Vi seroconversion episodes in serological surveillance were 2505 episodes (95% CI 1605–3727) in Blantyre, 7631 (95% CI 5913–9691) in Kathmandu, and 3256 (95% CI 2432–4270) in Dhaka.423 618 individuals were included in the demographic census, contributing 626 219 person-years of observation for febrile illness surveillance. 624 High disease incidence and rates of antimicrobial resistance were observed across three different transmission settings and thus necessitate multiple intervention strategies to achieve global control of these pathogens.Wellcome Trust and the Bill & Melinda Gates Foundation. Salmonella enterica serovars Typhi (S Typhi) and Paratyphi A, B, and C cause enteric fever, which presents as a non-specific febrile illness after the oral ingestion of contaminated food or water, with a reported case fatality rate of around 2·5% despite antimicrobial treatment.S Paratyphi A in some sites.S Typhi, often associated with large outbreaks, persisting for years, at multiple African sitesEnteric fever is estimated to cause 11–18 million infections and 100 000–200 000 deaths globally each year, resulting in a considerable public health burden in many low-income and middle-income countries in Africa and Asia.Various factors lead to underestimation of the true incidence of disease, including the non-specific presentation of the disease,Evidence before this studySalmonella enterica serotype Typhi (S Typhi).We considered evidence from a systematic review of typhoid fever incidence studies published in February, 2017, in addition to a PubMed search for articles done on Jan 1, 2021, using the search terms “ AND seroincidence”. Our search yielded 33 studies from sites in 21 countries that had reported on the incidence of blood-culture-confirmed typhoid fever. No population-based incidence studies of enteric fever have been done in Malawi or Nepal. Two previous studies done in Dhaka, Bangladesh reported typhoid fever incidence estimates of 395 cases per 100 000 person-years for the period 2000–01 and 280 cases per 100 000 person-years for the period 2003–04. No previous studies have estimated the seroincidence of infection with Added value of this studyS Typhi infection on the basis of serial anti-Vi IgG titres. We found a high incidence of typhoid fever, with overall crude and adjusted incidence of blood-culture-confirmed S Typhi per 100 000 person-years of observation of 58 cases (95% CI 48–70) and 477 cases  in Blantyre, 74 (95% CI 62–87) and 1065 (95% CrI 687–1824) in Kathmandu, and 161 (95% CI 145–179) and 1138 (95% CrI 889–1477) in Dhaka, respectively. Seroconversion rates for S Typhi infection per 100 000 person-years estimated from anti-Vi seroconversion episodes in serological surveillance were 2505 (95% CI 1605–3727) in Blantyre, 7631 (95% CI 5913–9691) in Kathmandu, and 3256 (95% CI 2432–4270) in Dhaka. Additionally, we found high rates of antimicrobial resistance across the three sites, with multidrug resistance identified in 44% of isolates and fluoroquinolone resistance identified in 61% of isolates.We provide the first population-based enteric fever incidence estimates for Blantyre, Malawi and Kathmandu, Nepal, and updated estimates of incidence in Dhaka, Bangladesh. This is also the first study to compare population-based estimates of typhoid fever incidence with estimates of the seroincidence of Implications of all the available evidenceS Typhi and S enterica serotype Paratyphi A, but patterns of resistance vary between sub-Saharan Africa and south Asia. Passive surveillance of blood-culture-confirmed enteric fever cases considerably underestimate the true incidence of the disease. Seroincidence data can complement traditional population-based surveillance of blood-culture-confirmed typhoid fever, but further research is needed to interpret the significance of increases in anti-Vi titres.The high burden of typhoid fever at these study sites provides evidence to support decision making on typhoid conjugate vaccine introduction in these countries. Paratyphoid fever is rarely observed in sub-Saharan Africa, but accounts for 5–25% of enteric fever cases in south Asia. Antimicrobial resistance is common among isolates of both S Typhi and S Paratyphi at three urban sites in Africa  and Asia  and seroconversion rates for S Typhi.Using data gaps identified through a typhoid transmission model,The STRATAA programme is a prospective observational, population-based collaborative and multidisciplinary epidemiological study, comprising health-facility-based passive surveillance for febrile illness, community-based serological surveys, and health-care utilisation surveys nested within a demographic household census . A detaiBriefly, the study was done in three urban areas within the Ndirande township of Blantyre, Malawi, the Lalitpur area of Kathmandu, Nepal, and Mirpur, Dhaka, Bangladesh. Further information on the study sites is provided in the Within a demarcated geographical area, a baseline census population was enumerated over a 3–5-month period . Consent and demographic information were collected from the head of the household. Each household and individual were given a unique household and member identification number and global positioning system (GPS) coordinates were recorded. A census update was done three times in Dhaka at intervals of 6 months and once in Kathmandu at 1 year, and all three sites had a final census at 2 years. All data were collected through Open Data Kit Collect using Android-based tablet devices, and stored on a MySQL database.Two health-care utilisation surveys were done at each site between 2016 and 2018. Approximately 735 households with children were interviewed per survey to estimate the probability that those with fever would seek health care at a designated study facility . HousehoParticipants within the demographic census area were encouraged to attend study health-care facilities for blood culture and treatment if they developed fever. Participants presenting from within the geographical census area were approached for recruitment if they had a history of fever for 72 h or more (later changed to ≥48 h) or current temperature of 38·0°C or higher .Approximately 8500 participants were randomly selected in an age-stratified manner from the original demographic census . Using GS Typhi, S Paratyphi, and non-typhoidal salmonellae.Microbiological culture of blood was done using an automated system  at all three sites following collection of a single aerobic bottle. For positive cultures exhibiting growth, organisms were then identified using colony morphology, Gram staining, standard biochemical tests, and specific antisera, with particular focus on the identification of Anti-Vi IgG titres in plasma collected from participants were measured using the commercial VaccZyme ELISA kit  according to the manufacturer's guidelines.S Typhi for blood-culture sensitivity, the probability of receiving a blood culture diagnostic test, and the probability of health-care-seeking using a Bayesian framework that incorporated both observed STRATAA data and information from the literature. Adjustments factors were site-specific and varied by age group.We calculated crude incidence rates by dividing the number of blood-culture-confirmed cases by the total amount of person-time observed in each age group and for the entire census population in each site; and estimated 95% binomial CIs. To account for the underestimation of typhoid fever incidence based on culture-confirmed cases, we adjusted the observed crude incidence rates of We defined seroconversion as a 2-fold increase in anti-Vi IgG titres and an absolute titre of 50 EU/mL or higher at the second timepoint to account for small variations above the lower limit of detection; the absolute titre threshold was based on baseline data from presumably unexposed participants in a human challenge model.The study funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.423 618 individuals residing in 99 033 households were included in the demographic censuses, contributing 626 219 person-years of observation for febrile illness surveillance  were enrolled from ten health-care facilities . Baseline characteristics for febrile patients are described in S Typhi , S Paratyphi A , and Salmonella enterica serovar Typhimurium . Blood-culture positivity rates for typhoidal pathogens (S Typhi and S Paratyphi A and B) were 3·2% in Blantyre, 6·6% in Kathmandu, and 8·2% in Dhaka. The overall contamination rate was 7·9% .Pathogenic bacteria were isolated from the blood cultures of 822 (6·8%) of 12 082 participants: 162 (4·5%) in Blantyre, 166 (6·9%) in Kathmandu, and 494 (9·2%) in Dhaka. The most common bacteria were The incidence of hospital admission for typhoid fever was higher in Blantyre  than in Kathmandu  and Dhaka , and deaths secondary to typhoid infection were only reported in Blantyre (two deaths [1·9%] among 105 cases). Previous antimicrobial usage and prescription of antimicrobials following blood-culture collection was significantly higher in blood-culture positive individuals than blood-culture negative individuals across all three sites .S Typhi infection was 58 cases (95% CI 48–70) per 100 000 person-years of observation in Blantyre, 74 cases (62–87) per 100 000 person-years of observation in Kathmandu, and 161 cases (145–179) per 100 000 person-years of observation in Dhaka  per 100 000 person-years of observation in Kathmandu and 42 cases (34–52) per 100 000 person-years of observation in Dhaka, with the highest incidence identified among individuals aged 5–9-years.Salmonella Typhimurium  was highest among individuals aged 2 years  and Kathmandu (127 [83%] of 153 isolates), but was only identified in a single isolate from Blantyre (one [<1%] of 115 isolates). Fluoroquinolone non-susceptibility was almost universal among S Paratyphi A isolates . In contrast, 92% of S Typhi isolates from Blantyre were multidrug resistant , whereas only 1% of isolates in Kathmandu and 39% of isolates in Dhaka were multidrug resistant. Azithromycin non-susceptibility was detected in both Asian sites but was not assessed in Blantyre. Azithromycin non-susceptibility was more frequent in S Paratyphi A  than S Typhi .The antimicrobial susceptibility profiles for both ach site . FluoroqS Typhi in the three sites  of 207 cases per 100 000 person-years of observation at the peak of the typhoid fever outbreak in 2013 in Blantyre.Disease incidence estimates for Africa have a greater level of uncertainty than estimates from Asia due to fewer population-based studies. A meta-analysis estimated adjusted rates of 620 cases per 100 000 person-years of observation for eastern sub-Saharan Africa and 1459 cases per 100 000 person-years of observation for central sub-Saharan Africa, although the estimates had wide CIs.S Paratyphi A in both Dhaka (117 cases per 100 000 person-years of observation) and Kathmandu (37 cases per 100 000 person-years of observation)S Paratyphi A were identified, but consistent with surveillance across Africa,S Typhimurium remains in the youngest children (observed incidence 117 cases per 100 000 person-years of observation among children aged 2 years).The surveillance data were consistent with other published data on the increasing importance of Salmonellae are on the WHO priority pathogen list due to the high rate of associated antimicrobial resistance and the risk this confers to human health.Salmonellae and the different antimicrobial resistance profiles of S Typhi and S Paratyphi A, and differences in antimicrobial resistance between Africa and Asia.S Typhi culture positive had substantially higher rates of antibiotic use before seeking health care and higher rates of antibiotic prescription at the time of heath-care facility visit, demonstrate the escalating risk of antimicrobial resistance associated with global typhoid management.Our findings demonstrate that adjustment factors cannot be applied universally to observed rates of blood-culture-confirmed disease across different epidemiological contexts and age groups. Use of alternative health-care facilities and pharmacies was higher at Asian sites than the African site, leading to higher inflation of incidence once adjusted, whereas in Blantyre, fewer individuals who sought health care at study facilities received a blood culture due to high incidence of febrile illness, inadequate health-care infrastructure, and parental refusal.In Blantyre, individuals with typhoid presented with more severe fever and a longer duration of fever, and hospitalisation was two times higher than at the other two sites. This difference might indicate that despite the adjustments for sampling and health-care seeking behaviour, undetected mild or subclinical disease remains an ongoing burden, consistent with the comparatively high rates of seroconversion observed at the Blantyre site. Such differences might also reflect differences in the immunological history of individuals across the three sites.S Typhi than provided by passive blood-culture surveillance. A cross-sectional seroepidemiological study from Fiji estimated seroprevalence of anti-Vi IgG antibodies to be higher than predicted based on blood-culture-confirmed disease.Measuring seroincidence, as described in this study, provides an alternative estimate of the rate of exposure to S Typhi across multiple sites. With the exception of the 10–14-year age group in Dhaka, all the age-specific seroincidence estimates either exceeded or had overlapping CIs with the adjusted incidence estimates from passive surveillance, such that seroincidence could be used as an upper bound for disease incidence within certain populations.This study is the first to use serological data to calculate seroincidence for S Typhi. The high rates of seroconversion among older individuals, particularly in Nepal, could be evidence of ongoing exposure and transmission within these age groups, which due to the high use of antimicrobials from community pharmacies, or partial immunity leading to subclinical infection, rarely requires hospital care.Quantifying the incidence of subclinical infections is also key to understanding the contribution of different age groups to the transmission of A marked difference was observed between the seroincidence estimates and the adjusted incidence estimates from passive surveillance across the three sites, with higher seroincidence rates in Kathmandu compared with Dhaka, in contrast to what was observed in passive surveillance. No established cutoff exists to define seroconversion, and anti-Vi antibody might not be the most accurate method of calculating seroincidence. Further work examining different typhoid antigens is ongoing.S Typhi infection is sensitive to the thresholds used to define seroconversion, which are based on scarce data. It is also possible that exposure to non-typhoidal organisms  could elicit these antibodies. Sixth, surveillance sites were chosen in urban areas with known high enteric fever incidence, and the geographical footprint and duration of surveillance was restricted. These factors together might reduce the generalisability of these data to other sites.This study has a number of limitations. First, due to the very large number of individuals attending health-care facilities, particularly in Blantyre, it was not possible to enrol all eligible participants. Second, due to the high number of private health-care facilities and pharmacies in both Dhaka and Kathmandu, our surveillance sites only captured a proportion of all febrile illnesses. Third, blood-culture sensitivity is only around 60% and is affected by previous antimicrobial use, volume of blood collected, and timing of blood collection in the natural history of infection. Sensitivity of blood culture is also affected by the contamination rate at collection, which was higher in Blantyre and Dhaka. Low sensitivity of blood culture is likely to result in underestimation of incidence based on blood-culture-confirmed cases, but we accounted for these factors in the adjusted estimates. Fourth, to encourage higher usage of study facilities, free treatment and care was provided within the census populations by study teams, to a variable extent at different sites. With improved diagnosis through the use of blood culture and appropriate prescription of antimicrobials, the hospital admission and complication rate might have been falsely lowered compared with other previously published observational data.Despite these limitations in the design of this study, nesting multiple surveillance methods within a demographic census allowed the weaknesses of individual methods to be contextualised in different settings, and varying populations to be characterised.S Paratyphi A.Our data support the WHO recommendation for introduction of typhoid conjugate vaccines for children from age 6 months. Catch-up campaigns are also likely to be cost-effective,Deidentified individual participant data and a data dictionary can be made available for passive surveillance, health-care utilisation, census, and census update data on request to the chief investigator (andrew.pollard@paediatrics.ox.ac.uk) with a research proposal and signed data usage agreement. A study protocol and statistical analysis plan have been published previously.VEP is a member of the WHO Immunization and Vaccine-related Implementation Research Advisory Committee. AJP chairs the UK Department of Health Joint Committee on Vaccination and Immunisation (JCVI) and is a member of the WHO Strategic Advisory Group of Experts. RSH is supported by the National Institute for Health Research (NIHR) Global Health Research Unit on Mucosal Pathogens using UK aid from the UK Government. The views expressed in this publication are those of the authors and not necessarily those of the UK Department of Health, JCVI, WHO, NIHR, or the Department of Health and Social Care. All other authors declare no competing interests.


We assessed the relationship between the multiple sclerosis (MS) disease-modifying drugs (DMDs) and healthcare use.Persons with MS (aged ⩾18 years) were identified using linked population-based health administrative data in four Canadian provinces and were followed from the most recent of their first MS/demyelinating event or 1 January 1996 until the earliest of death, emigration, or study end (31 December 2017 or 31 March 2018). Prescription records captured DMD exposure, examined as any DMD, then by generation (first-generation (the injectables) or second-generation ) and individual DMD. The associations with subsequent all-cause hospitalizations and physician visits were examined using proportional means model and negative binomial regression.Of 35,894 MS cases , mean follow-up was 12.0 years, with person-years of DMD exposure for any, or any first- or second-generation DMD being 63,290, 54,605 and 8685, respectively. Any DMD or any first-generation DMD exposure (versus non-exposure) was associated with a 24% lower hazard of hospitalization : 0.71–0.82), rising to 29% for the second-generation DMDs . This ranged from 18% for teriflunomide  to 44% for fingolimod . In contrast, DMD exposure was generally not associated with substantial differences in physician visits.Findings provide real-world evidence of a beneficial relationship between DMD exposure and hospitalizations. However, in clinical practice, DMDs are used in the wider MS population. A recent study showed that nearly 20% of people with MS had some comorbidity and approximately one in six were aged ⩾50 years when first receiving a DMD. However, such individuals are typically excluded from clinical trials. Understanding the benefits of the DMDs in the broader MS populations treated in the “real-world” setting is needed for therapeutic-related decision-making. Health service use, particularly hospitalizations, represents a major burden for society, patients, and families. Population-based longitudinal studies of health care use are needed to assess the benefits of the DMDs and facilitate healthcare planning. Prior studies have not been population-based, have been limited to private health insurance enrollees5 or were ecological in design and unable to assess DMD use at the individual patient level.7Disease-modifying drug (DMD) efficacy is typically established after short clinical trials in highly selected multiple sclerosis (MS) patients.We investigated the relationship between DMD exposure and health service use in a MS population using individual patient-level linked administrative data collected over a 22-year period. were linked for each individual resident within each province. The administrative data included the following: physician and hospital data,10 capturing all physician visits and hospitalizations, coded using the International Classification of Diseases (ICD) system; the provincial health insurance registries, capturing demographic information ; and vital statistics data, capturing death records in British Columbia/Nova Scotia. Prescription data provided all pharmacy dispensed prescriptions . In Nova Scotia, the Dalhousie MS Research Unit database provided DMD prescription start and stop dates.This was a multi-region, population-based observational study. Multiple administrative health data-bases covering four provinces , representing nearly 25% of Canada’s population, Once identified, cases were assigned an index date, defined as the most recent of the first MS or related demyelinating disease code captured in the physician/hospital data or first MS DMD prescription filled (Supplementary Tables 1–2); an individual’s 18th birthday; or 1 January 1996 (British Columbia), 1 April 1996 (Manitoba), 1 January 1997 (Saskatchewan), or 1 January 1998 (Nova Scotia). These dates represent the first availability of prescription data (including the MS DMDs), and first full year of government financial coverage of the DMDs. One year of provincial residency pre-index date was required; all identified persons with MS were followed from their index date until the earliest of death, emigration, or study end  and 31 March 2018 (Saskatchewan) based on the last availability date).We identified MS cases using a validated algorithm (⩾3 MS diagnostic codes (ICD-9/10 340/G35) or ⩾1 dispensation of a DMD).—were described at the index date. Comorbidity in the year pre-index date was measured using the Charlson Comorbidity index (excluding hemiplegia and paraplegia to avoid misclassifying MS symptoms).Cohort characteristics—sex, age, calendar-year, and socioeconomic status Supplementary Table 2, including the year of each DMD’s approval for use in MS by Health Canada. Briefly, the first-generation DMDs included the injectables (i.e. beta-interferon and glatiramer acetate), and the second-generation included the infusions and orally administered DMDs. DMD exposure periods were determined based on the number of days supplied , or the quantity dispensed (Saskatchewan), or the DMD start/stop dates (Nova Scotia). Discontinuation was defined as no further dispensations for that DMD (lasting ⩾90 consecutive days), plus a 30-day grace period ; that is, discontinuation date = last DMD dispensed date + days supplied + 30 days. Except for alemtuzumab and ocrelizumab, whereby a person was considered exposed for a full 12- or 6-month post-dispensation, respectively, and discontinued thereafter if no further dispensations (plus the 30-day grace period).First- and second-generation DMD availability over the study period is shown in An individual’s exposure status could change over time (i.e. time-dependent variable) and was assessed as periods of any exposure or no exposure, then by generation and individual DMD. To avoid double counting, any new hospitalization occurring within 24 hours  were considered one event. Evidence of >1 identical physician visit-related ICD code on the same day was considered one visit.The primary and secondary outcomes were all-cause hospitalizations (events) and number of all physician service use (visits), respectively. Hospitalizations included day surgery, but not infusions . and neurologist specialty-specific physician visits (as their frequency is expected to be higher in persons using a DMD (versus not using), as per standard of care, and could result in the overestimation of healthcare use related to DMD prescribing).Not counted as outcomes were pregnancy-related hospital or physician visit ICD codes (since DMD discontinuation is common during pregnancy)Data were analyzed within each province using a common approach. Aggregated results were combined using random-effects meta-analyses. We assessed the association between DMD exposure and (1) all-cause hospitalizations using a recurrent events proportional means model with robust sandwich variance estimates and (2) physician visits using a negative binomial regression model fitted by generalized estimating equations with exchangeable working correlation matrix. Findings were expressed as hazard or rate ratios, with 95% confidence intervals (CIs). These approaches allow for multiple events analyses for each participant while accounting for dependence of events. For hospitalizations, because an individual cannot be at risk of a second hospitalization while already hospitalized, the hospital stay was excluded from the follow-up period. For physician visits, the number were counted yearly, or by periods of DMD exposure, if changes in DMD use occurred within a 1-year period; an offset (log(days within each time period)) was specified to account for the variable length of periods. All models were adjusted for sex and socioeconomic status at the index date. Age, Charlson comorbidity score, and calendar-year were adjusted for as time-dependent covariates, updated on a yearly basis . The “DMD-unexposed” period formed the reference category for the main analyses, although the pairwise comparisons between DMDs  were reported from the same models as an exploratory approach. Crude rates per 100 person-years of follow-up were described.Complementary sex and physician specialty-specific analyses were performed. The latter was applied to the physician visits only, with crude rates by person-years of follow-up described for each DMD, and during periods of no exposure. In the largest province only, British Columbia, neurologist specialty was included in the count of all physician visits as a complementary approach. SAS V.9.4 and R V.4.0.2 were used for analyses. Approximately 30% of our study population were exposed to a DMD during follow-up, and this estimate falls within the ranges reported in other population-based observational studies over a comparable time period. The total person-years of follow-up while exposed to any DMD was 63,290 ; any first-generation DMD was 54,605  and any second-generation DMD was 8685 .A total of 35,894 MS cases were identified; most were female (72%) and the mean age at index date was 44.6 (standard deviation (SD) = 13.6) years . Cohort Exposure to any (versus no) DMD was associated with a 24% lower hazard of hospitalization : 0.71–0.81). Similarly, for the first-generation DMDs, a 24% lower hazard was observed, with a 29% lower hazard for the second generation . VariatiOverall, while exposure to any (versus no) DMD was associated with a lower rate of physician visits, this was modest and did not reach significance . A similar pattern was observed for exposure to a first- or second-generation DMD and for most of the individual DMDs . Only glWhen the DMDs were directly compared to each other, for hospitalizations, there was no significant difference between second- and first-generation DMDs . When assessed by individual DMD, no differences were evident when the first-generation (beta-interferon or glatiramer acetate) were each compared to each of the other DMDs . For theFor physician visits, while there was no significant difference for the second- versus first-generation DMDs , rates differed by individual DMD . For exaThe direction of findings was generally similar for both sexes, although some estimates were more pronounced (lower) for males  and 4. FSupplementary Figure 1).Crude rates of physician visits varied by individual DMD and relative to periods of no exposure . FingoliWe examined the relationship between DMD exposure and health service use in a large population of individuals with MS in a universal healthcare setting, spanning >20 years. Exposure to any first-generation DMD was associated with a 24% lower hazard of hospitalization compared to no exposure, rising to 29% for the second-generation DMDs. Variation was seen across the individual DMDs, but all findings were suggestive of lower hospitalizations, ranging from 18% for teriflunomide to 44% for fingolimod. In contrast, DMD exposure  versus no exposure was generally not associated with substantial differences in the overall rate of physician visits. Our study provides real-world evidence of a beneficial relationship between DMD exposure and hospitalizations.22 Conversely, the DMDs are associated with various adverse events (AEs), including rare, but severe, events which may also pose a risk for hospitalization or may require regular physician visits for management and monitoring. We found relatively few studies with which to compare our findings.425 For example, two studies  took a broad ecological approach and examined the relationship between DMD and healthcare use at the population rather than individual level.7 In Saskatchewan, as the overall number of filled DMD prescriptions increased all-cause hospitalizations decreased (1997–2016), while there was no relationship with the number of physician service claims. In Finland, a 4% annual reduction in MS-related hospitalizations (2004–2014) coincided with the increased availability and utilization of the DMDs. Which individual DMDs were contributing to these patterns was not examined in either study.7 Two US studies  accessed data spanning a 2-year period on select groups of people with private insurance.5 They found a lower proportion of people hospitalized in the year after (versus before) DMD initiation. Neither study could assess whether participants left the insurance plan during follow-up and data beyond 2 years were unavailable.5 A third US-based study of Medicare enrollees reported fewer all-cause hospitalizations related to DMD use; however, interpretation of findings is limited due to its cross-sectional design and 1-year study period.The relationship between DMD exposure and healthcare use may be explained by several factors. The DMDs have been shown to reduce the frequency and severity of relapses, which in turn could lower the risk of hospitalization. This could mean that patients with more active disease might be exposed to natalizumab, which could result in more hospitalizations due to underlying disease activity. Some studies have compared natalizumab with fingolimod in relation to effectiveness, assessed by relapse rates and disability progression, but the findings have been mixed; few studies reported no differences,27 while others concluded that natalizumab seemed more effective than fingolimod, at least over the short term.29 Exposure to two DMDs—alemtuzumab and teriflunomide—was associated with higher rates of physician visits in our study. Rates were 19%–34% higher for alemtuzumab compared with each of the other DMDs, which likely reflects the intensive (monthly) monitoring and laboratory testing required. Whereas for teriflunomide, rates were 10%–12% higher relative to glatiramer acetate, natalizumab, and fingolimod. For example, teriflunomide requires frequent blood tests, especially during the first 6 months of treatment, while glatiramer acetate does not. Frequent laboratory testing can also result in incidental findings, unrelated to DMD, which in turn may necessitate further investigations and physician visits. Teriflunomide has been shown as less efficacious and less effective than either fingolimod or natalizumab in managing disease activity, which might also partly contribute to our observations. Thus, it is plausible that any increases in safety monitoring may be counterbalanced by a decrease in the need for physician services related to drug (in)effectiveness.Interesting differences emerged when the individual DMDs were directly compared to each other as an exploratory approach. For example, of the second-generation DMDs, natalizumab was associated with higher hazard of hospitalization versus two of the oral DMDs (fingolimod and dimethyl fumarate). Our findings might reflect natalizumab’s status as a second-line treatment in Canada; it is typically reserved for patients with an inadequate response to another DMD due to its risk-benefit profile. Alemtuzumab exposure was associated with high rates of general practitioner and internal medicine visits, likely reflecting the regular safety-related monitoring required and its AE profile, including risk of autoimmune disease. Why alemtuzumab was also associated with high rates of psychiatric visits was less clear. A systematic review found no significant association between any individual DMD, including alemtuzumab , and an increased risk of adverse psychiatric effects.We also examined crude rates of physician services by specialty. Exposure to fingolimod was associated with relatively high rates of ophthalmologist visits, which would concur with the recommendation for regular ocular assessments and risk of macular edema.37 A 2018 review found that the majority (65%) of MS clinical trials did not pre-plan a sex-specific analysis. Of those that did, only efficacy was examined (not harms) and while most found no sex differences, studies may have lacked sufficient statistical power as relatively few males were included.37 Although males comprised approximately 30% of individuals in our study, our cohort was sizable. Nonetheless, our cohort was insufficient to reliably examine sex differences for the more recent DMDs.Although our findings were generally similar for both males and females, there was some suggestion that the effects were more pronounced for males. We were unable to find another study with which to compare these sex-specific findings. DMD-related sex differences appears poorly understood, despite well-recognized sex-differences in pharmacokinetics/pharmacodynamics. Nonetheless, we were able to account for several important factors which may influence treatment decisions and outcomes, such as socioeconomic status, sex, age, comorbidity burden, and calendar-year over time. We used a time-dependent approach when examining DMD exposure, which accounts for the changing treatment status of persons over time . It could be value for future studies to explore different ways of grouping the DMDs (e.g. by relative efficacy or by mechanism of action). Other study strengths included avoidance of selection bias (by accessing objectively collected population-based data) and a long follow-up duration. The universal healthcare setting allowed us to provide a comprehensive evaluation of health service utilization, including all hospital admission, physician visits, and filled prescriptions, regardless of a person’s ability to pay. Few world regions have access to such comprehensive, linked administrative health data for the entire population at the individual level.Our study has several limitations. While administrative health data offer opportunity to examine the patterns of health service utilization in the MS population at the individual level, these patterns should be interpreted accordingly; health services use may reflect, in part, a balance between the potential harms and benefits of the DMDs and should not be interpreted as only representing one or the other. We were not able to consider MS-specific clinical characteristics, such as relapses or disability which are not captured in the administrative data. Despite adjusting for several demographic characteristics and comorbidity, it is possible that comparisons between individual DMDs were influenced by underlying clinical features or other unmeasured confounders. For example, patients with more active disease might be treated with a higher efficacy DMD, but might also have required frequent physician visits or inpatient management due to their underlying disease. However, our complementary analyses, in which we included neurologist visits, did not change interpretation of findings. We had limited power to assess some of the newer second-generation DMDs which did not become widely available until close to our study end. Consequently, for DMDs such as alemtuzumab, the total person-years exposed was modest. We did not explore cause-specific events as, particularly for hospitalizations, modest number of events would prevent generation of reliable estimates. Other information such as lifestyle behaviors (e.g. smoking) or race/ethnicity or access to DMD as part of a clinical trial were not available. For example, aside from a very small number of individuals that may have enrolled in a clinical trial and been randomized to receive a DMD, most individuals would not have been on a DMD before the index date.We found in our study that periods of exposure to any DMD, or any first- or second-generation DMD, were associated with a lower hazard of hospitalization relative to no DMD exposure. However, there was substantial variation across the individual DMDs, particularly for the second-generation DMDs. In contrast, the relationship between DMD exposure with overall rates of physician visits was rather modest. Our study provides real-world insights into the beneficial effects of different DMDs on hospitalizations for people living with MS.Click here for additional data file.Supplemental material, sj-docx-1-msj-10.1177_13524585211063403 for Disease-modifying drugs for multiple sclerosis and subsequent health service use by Huah Shin Ng, Feng Zhu, Elaine Kingwell, Yinshan Zhao, Shenzhen Yao, Okechukwu Ekuma, Lawrence W Svenson, Charity Evans, John D Fisk, Ruth Ann Marrie and Helen Tremlett in Multiple Sclerosis Journal


Between 2011 and 2019, the proportion of high schoolstudents who were current e-cigarettes users increased from 1.5% to 27.5%.4 examines theassociations of the COVID-19 pandemic with patterns of youth e-cigarette use, drawing ona national sample of 2167 underage youth and young adults sampled between May 6 and 14,2020. Among the key findings of the study were that more than half of participants (1198[56.4%]) reported change in their e-cigarette use since the beginning of the COVID-19pandemic. Among 1197 participants reporting on the type of change, one-third of youth(388 participants [32.8%]) quit vaping, and another one-third (422 participants [35.3%])reduced their use of e-cigarettes, with the remaining youth either increasing their useor switching to other nicotine or cannabis products. Second, the point of purchasinge-cigarettes changed markedly before and after the COVID-19 pandemic, with approximately20% of youth e-cigarette users switching from retail stores to online sources. Third,the study examined factors associated with continuing to vape through the pandemic,finding that higher nicotine dependence, e-cigarette use frequency, poor online ageverification, and several other factors were associated with sustained use ofe-cigarette products.The coronavirus disease 2019 (COVID-19) pandemic has had far-reachingconsequences since emerging in the US in February 2020. This new study by Gaiha andcolleagues4 of substantial declines in e-cigarette use associated withCOVID-19 is consistent with other emerging evidence. Data from the 2020 National YouthTobacco Survey (NYTS)1 indicate thatapproximately 20% of high school students and 5% of middle school students were currentusers of e-cigarettes in early 2020, compared with 27.5% of high school students and10.5% of middle school students in 2019. These data, collected between January 16 andMarch 16, 2020 suggest that substantial declines in e-cigarette use may have occurredeven prior to the period of the study by Gaiha et al4 and in some cases before stay-at-home orders came intoeffect.The findings in the study by Gaiha et al4 inquired about the reasonsfor decreased use. Explanations for decreased use included at home and parents will know(136 participants [15.2%]), cannot get products (175 participants [19.5%]), e-cigarettesmay weaken lungs (224 participants [25.0%]), any combination of these factors (287participants [32.1%]), and other (73 participants [8.2%]). These breakdowns point to theroles of both supply-and demand-side factors in shaping patterns of e-cigarette useduring the COVID-19 pandemic. With respect to the supply side, reduced access toproducts was an important factor, and on the demand side, participants’perceptions regarding health consequences of e-cigarette use appeared to change . The fact that one-quarter of youth reportedconcerns regarding health effects of e-cigarette products as a major motivating factorfor quitting or reducing e-cigarette use indicates that targeted educational campaignsmay be a fruitful strategy for further reducing youth vaping. Such efforts may be madeespecially compelling by communicating potential associations of vaping with incidenceand fatality of COVID-19, a link that is supported by emerging literature, such asanother 2020 study by Gaiha et al.5Among 895 participants who decreased or quit use of e-cigarettes, Gaiha etal4 alsoreported that purchasing of e-cigarettes shifted increasingly online. This is consistentwith emerging qualitative evidence by Schiff et al6 that online retailers are frequently accessible to underageyouth and that even when age verification is in place, it is often easily circumvented.The shift toward online purchasing highlights a critical need for the Food and DrugAdministration to use its regulatory authority to prohibit online sales to underageyouth and requiring a strict burden of proof by e-cigarette companies of their ageverification systems at the time of applying for market authorization.In this study, Gaiha et al4 These findings mayin part reflect the lack of comprehensive addiction services for youth who vape or alack of awareness of existing services. Additional research is required to understandthe effectiveness of different approaches to addressing youth vaping addiction,including programs using novel approaches, such as social media, virtual reality, andtext message programs. Further work on how to deliver these programs at scale, given themagnitude of youth vaping in the US, is also needed.Perhaps not surprisingly, youth with more frequent e-cigarette use and highernicotine dependence were more likely to continue vaping during the COVID-19pandemic.4 indicate that reductions in youth vaping were not greater inunderage youth compared with older youth who were aged 21 years and older, despiteunderage youth having experienced greater restrictions on use in their homeenvironments. In fact, the least cited reason for decreased use of e-cigarettes duringthe COVID-19 pandemic was that parents will know, suggesting an ability to usee-cigarette products discretely, even in the home environment. As Gaiha et al4 point out, these findings point to acritical need to regulate how e-cigarettes are designed to render them less discrete andmore difficult to conceal.The results reported by Gaiha et al4 may be temperedby the possibility that use will rebound to pre–COVID-19 levels as the COVID-19pandemic eventually recedes. However, the findings from the study by Gaiha etal4 highlight several insightsinto how we might ensure that the declines remain durable. First, Gaiha et al4 suggest that youth were responsive toconcerns regarding the health effects of vaping, especially in the context of risks forCOVID-19 morbidity; thus, it is imperative that the evolving evidence on e-cigaretteharms is widely disseminated through social media and other avenues. Second, ase-cigarette purchases shift to online sales, it is important to impose strongersafeguards, including more stringent age verification, while also taking measures torestrict access at conventional purchasing points, such as gas stations and vape shops.Third, to maintain the reductions that have occurred and to prevent relapse of youth whoformerly vaped, it is essential that robust addiction services be put in place toprovide the necessary services for youth struggling with nicotine addiction. Together,these measures may go a long way toward ensuring that the declines in e-cigarette useobserved during the COVID-19 pandemic are maintained into the future.Optimism regarding the significant declines in e-cigarette use observed in thestudy by Gaiha et al


Introduction: Many severe COVID-19 patients require respiratory support and monitoring. An intermediate respiratory care unit (IMCU) may be a valuable element for optimizing patient care and limited health-care resources management. We aim to assess the clinical outcomes of severe COVID-19 patients admitted to an IMCU.Methods: Observational, retrospective study including patients admitted to the IMCU due to COVID-19 pneumonia during the months of March and April 2020. Patients were stratified based on their requirement of transfer to the intensive care unit (ICU) and on survival status at the end of follow-up. A multivariable Cox proportional hazards method was used to assess risk factors associated with mortality.Results: A total of 253 patients were included. Of them, 68% were male and median age was 65 years (IQR 18 years). Ninety-two patients (36.4%) required ICU transfer. Patients transferred to the ICU had a higher mortality rate . Multivariable proportional hazards model showed that age ≥65 years ; chronic respiratory conditions  and chronic kidney disease  were independently associated with mortality. High-dose systemic corticosteroids followed by progressive dose tapering showed a lower risk of death .Conclusions: IMCU may be a useful tool for the multidisciplinary management of severe COVID-19 patients requiring respiratory support and non-invasive monitoring, therefore reducing ICU burden. Older age and chronic respiratory or renal conditions are associated with worse clinical outcomes, while treatment with systemic corticosteroids may have a protective effect on mortality. Coronavirus disease 2019 (COVID-19) is a respiratory condition caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) . In thisIntermediate respiratory care units (IMCU) are a useful resource for the management of complex patients that do not require admission to the ICU, invasive mechanical ventilation or invasive monitoring . IMCU caTo this date, there have been more than 158 million reported cases worldwide, with over 3 million deaths . MortaliWe aim to evaluate the outcomes of severely ill COVID-19 patients requiring monitoring and/or non-invasive respiratory support admitted to an IMCU, and to identify clinical factors that may have led to these results.An observational and retrospective study was performed on consecutive patients admitted to the IMCU of a tertiary care hospital in Barcelona (Spain) throughout the months of March and April 2020. The final date of follow-up was June 28, 2020. Study protocol was approved by the local ethics committee (No. PR260/20). Inclusion criterion was admission to IMCU due to respiratory failure related to COVID-19 pneumonia requiring non-invasive monitoring and/or non-invasive respiratory support. Patients were diagnosed with a positive polymerase chain reaction for SARS-CoV2 from nasopharyngeal swab and the presence of pulmonary opacities on chest X-ray. According to local protocol, IMCU admission was limited to subjects with an oxygen saturation (SpO2) to inspired oxygen fraction (FiO2) ratio lower than 200 but not expected to require immediate support with invasive mechanical ventilation. Subjects were admitted directly from the emergency department or transferred from a regional hospital or general wards due to clinical impairment. Exclusion criteria were: recent admission to the ICU, as these patients had already shown clinical improvement, subjects with COVID-19 pneumonia not requiring oxygen support through HFNC or NIV, and respiratory failure due to any etiology other than COVID-19. Demographic, clinical, radiological and laboratory data were collected from electronic medical records for all patients at the time of IMCU admission. All participants were treated according to hospital protocols. Systemic corticosteroid therapy was divided into four categories depending on dose and administration route, as patients were treated before preliminary results from the RECOVERY trial : (a) no t test or their corresponding non-parametrical tests  were used to evaluate their differences, when required. Kaplan–Meier curves were used for the survival analysis. In order to identify factors associated with mortality, a multivariable Cox proportional hazards analysis was performed including significant variables from univariate analysis. A p-value < 0.05 was considered statistically significant. Data were analyzed using R (software version 3.6.2).Frequency and percentages were used to present categorical data, and chi-squared test or Fisher's exact test were used to evaluate their differences. Continuous variables are expressed as mean and standard deviation (SD) for normally distributed variables or median and interquartile range (IQR) otherwise. ANOVA and Student's A total of 291 patients were admitted to the IMCU during the months of March and April of 2020 due to COVID-19 pneumonia. After excluding 38 patients that were previously treated in the ICU, 253 patients were finally included. Of them, 68% were male and median age was 65 years (IQR 18 years). The most frequent comorbidities were hypertension (50.2%), dyslipidemia (47.8%) and diabetes mellitus (29.6%). Demographic and clinical characteristics of included patients at admission to IMCU are described in Ninety-two patients (36.4%) required transfer to the ICU. There were no significant differences in age, gender or comorbidities between ICU and non-ICU groups. However, patients requiring ICU management had higher systemic inflammatory markers and a significant lower SpO2/FiO2 ratio on admission. A comparison of patient characteristics between those that were admitted to the ICU and those who did not, is shown in p < 0.001). However, a similar proportion of subjects needed admission to socio-health centers or transfer to their regional hospital for convalescence. Six patients of the ICU group were still hospitalized, while none of the IMCU subjects were in the hospital at the end of follow-up. A comparison of clinical outcomes between groups is presented in A higher proportion of patients received home discharge in the IMCU group compared to those that required transfer to ICU . When comparing survivors and non-survivors, a significant difference was observed regarding age . Non-survivors had a higher proportion of comorbidities such as dyslipidemia, chronic respiratory diseases and chronic kidney disease. Furthermore, these patients had higher blood leukocyte counts, serum lactate dehydrogenase (LDH), C-reactive protein and D-dimer, and lower blood lymphocyte counts on admission to the IMCU (Eighty patients (31.6%) died during hospitalization. Main causes of death were ARDS and septic shock. Patients requiring transfer to the ICU had a higher mortality rate . Nevertheless, similar proportions of gender, comorbidities and laboratory findings on admission were observed between groups.We compared groups of deceased patients. Subjects who died at the IMCU were significantly older  and chronic kidney disease . Patients receiving high dose systemic corticosteroids followed by or progressive dose tapering showed a significant lower risk of death . Regarding laboratory findings on admission, blood leukocyte counts higher than 10 × 109/L and lymphocyte counts lower than 0.4 × 109/L were associated with higher risk of death . Furthermore, serum LDH higher than 445 U/L was also independently associated with mortality . Variables that independently increased risk of death in the multivariable Cox proportional hazards analysis included: age equal or older than 65 years [hazard ratio (HR) 4.14; 95% confidence interval (CI) 2.31–7.42; This is one of the first and largest studies to assess the clinical outcomes of severe COVID-19 patients admitted to an IMCU during the first wave of the pandemic. The IMCU allows a secure environment for providing non-invasive respiratory support and patient monitoring, potentially improving healthcare resource management. Our patient model management, including continuous assessment by specialists of respiratory medicine, critical care and internal medicine showed relatively low mortality rates and positive clinical outcomes compared to results from other critical care cohorts. Factors associated with higher mortality in these patients were older age, chronic pulmonary or kidney diseases, while treatment with systemic corticosteroid treatment was protective.Patient characteristics and clinical presentation of the disease were similar to what has been described in previous studies , 18–20. All-cause mortality in our cohort was 31.6%, similar to what has been observed in other cohorts. A recent study by Li et al. showed that mortality in severe cases was 32.5% during the 32 days follow-up period, regardless of respiratory support requirement . Also, tSurvival analysis showed significant differences between patients of 65 years of age or older, and in those with chronic renal and respiratory diseases. These conditions were identified as independent risk factors for in-hospital mortality. Older age has been associated with an increase in the risk of death in several previous studies –20, 23. Concerning patient treatment, only systemic corticosteroids were independently associated with a reduction of mortality in our cohort. Subjects receiving 3 days of high-dose methylprednisolone or dexamethasone followed by 7 days of oral dose tapering had a lower risk of death than those who received shorter treatments or were not treated. The positive effect of systemic corticosteroids has been described in recent studies. In a cohort from Wuhan, patients treated with methylprednisolone had a lower mortality rate . Also, aThis study has several limitations, mainly related to the retrospective design of the analysis including a single center. The lack of a control group  does not allow to directly quantify the impact of IMCU in COVID-19 mortality or health-care burden. Also, our cohort included only severe patients, as we focused on the role of IMCU in patient management. This may limit the generalization of our results to less severe cases. Furthermore, local treatment protocols changed during the inclusion period due to the pandemic situation and the scarce data on COVID-19, which may have influenced the clinical outcomes of our study. However, the number of participants is higher than most previous studies, and our results agree with observations from different cohorts.Our study shows that IMCU may be useful tools for the multidisciplinary management of severe COVID-19 patients requiring non-invasive respiratory support and monitoring, therefore helping to reduce ICU burden. Older age and chronic respiratory or renal conditions are associated with worse clinical outcomes while treatment with systemic corticosteroids may have a protective effect on mortality. These results may help to further validate the feasibility of IMCU during the COVID-19 pandemic.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Bellvitge University Hospital Ethics Committee. Study reference No. PR260/20. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.GS-C and MG participated in study design, acquisition, analysis, and interpretation of data, and in the elaboration of the manuscript. GB participated in data acquisition and in the elaboration of the manuscript. YR participated in data acquisition, analysis, and interpretation of data. MH-A, AM, PT-S, AC, EC, MS, AA, NR, and CS participated in data acquisition and analysis. JS participated in data acquisition, analysis, and interpretation of the results. MM-M participated in study design, interpretation of data, and in the elaboration of the manuscript. SS participated in study design, interpretation of data, and in the elaboration of the manuscript. All authors read and approved the final manuscript.GS-C reports grants from Grifols. MM-M reports grants from Boehringer Ingelheim, Roche, Glaxo-Smith-Kline, Esteve-Teijin, Almirall, and Chiesi outside the submitted work. The remaining 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.


Glioblastoma is the most common primary brain tumor in adults, and its aggressive nature yields a poor prognosis despite current treatment strategies. The aim of our literature review is to discuss various immunotherapeutic strategies currently being investigated in the treatment of glioblastoma. Checkpoint inhibitors, various vaccination strategies, and CAR T-cell therapies serve as some of the most investigated immunotherapeutic strategies. However, all strategies face various limitations, such as the low relative mutational burden, the immunosuppressive tumor microenvironment, and genetic heterogeneity, which serve as the current challenges.Glioblastoma (GBM) is a lethal primary brain tumor. Despite extensive effort in basic, translational, and clinical research, the treatment outcomes for patients with GBM are virtually unchanged over the past 15 years. GBM is one of the most immunologically “cold” tumors, in which cytotoxic T-cell infiltration is minimal, and myeloid infiltration predominates. This is due to the profound immunosuppressive nature of GBM, a tumor microenvironment that is metabolically challenging for immune cells, and the low mutational burden of GBMs. Together, these GBM characteristics contribute to the poor results obtained from immunotherapy. However, as indicated by an ongoing and expanding number of clinical trials, and despite the mostly disappointing results to date, immunotherapy remains a conceptually attractive approach for treating GBM. Checkpoint inhibitors, various vaccination strategies, and CAR T-cell therapy serve as some of the most investigated immunotherapeutic strategies. This review article aims to provide a general overview of the current state of glioblastoma immunotherapy. Information was compiled through a literature search conducted on PubMed and clinical trials between 1961 to 2021. Glioblastoma (GBM) is the most malignant of the glial tumors (grade IV) and represents more than half of all primary brain tumors in the United States, with an annual prevalence of roughly 3.19 per 100,000 people . GBMs pr2) with concomitant radiotherapy (RT) (60 Gy) for 42 days followed by six cycles of adjuvant TMZ (150 to 200 mg/m2) administered for five days during each 28-day cycle [The Stupp protocol remains the standard of care for GBM, with virtually no improvements since it was developed in 2005. The Stupp protocol entails the administration of temozolomide (TMZ)  have been highlighted in numerous studies ,14,15,16Checkpoint inhibitors are tumor-directed monoclonal antibodies that have established therapeutic efficacy in the treatment of various solid tumors such as lung, head-and-neck, and renal cancers in addition to melanoma ,23,24,25Durvalumab (durva) is a human IgG1 monoclonal antibody that specifically targets PD-L1. Durva has already been approved in the treatment of non-small cell lung cancer in addition to bladder cancer in select patients ,33. A phAside from the Checkmate 143 phase III trial, ORR has been demonstrated in two other checkpoint inhibitor studies ,37. A siOngoing trials continue to investigate CTLA-4, PD-1, and other potential checkpoint inhibitors such as indoleamine 2,3-dioxygenase (IDO). IDO is an endogenous enzyme that plays an important role in the regulation of the immune system functioning to augment suppressor activity of regulatory T-cells and consequently inhibit CD8+ T-cells ,41. Stud2 following surgery and chemoradiation. Around 370 patients were randomized into each arm, and at the final analysis, there was no significant difference in overall survival for patients with MRD. This was unexpected due to the multiple, independent phase II trials that seemed to suggest benefits from the use of rindopepimut [Vaccination is another method in immunotherapy in which a tumor-specific response is provoked with the use of a foreign antigen. Vaccines can be either cell or peptide-based, and both types have been successfully investigated in clinical trials. Rindopepimut is a peptide-based vaccine targeting the EGFR deletion mutation in variant III of the epidermal growth factor receptor (EGFRvIII), commonly seen in GBM. It was first studied in the single-group phase II trial ACTIVATE, where 100 patients with EGFRvIII positive GBM were given rindopepimut alone, following gross total resection and lack of progression, following standard treatment of radiotherapy with concomitant temozolomide . This waopepimut .Another peptide-based vaccine being investigated in the treatment of GBM utilized the Wilm’s tumor (WT1) gene. The WT1 gene plays an important role in controlling cell proliferation and apoptosis. The WT1 gene is a widely recognized oncogene that is overexpressed in various solid malignancies ,52,53. IThe IDH1 peptide and Survivin are the other two molecules being investigated in peptide-based vaccines. SurVaxM(SVN53-67/M57-KLH) is a peptide vaccine synthesized to target survivin, a protein that aids in the inhibition of apoptosis. Survivin is expressed on GBM tumors and is associated with a poor prognosis ,59. TherIn the past decade, targeting multiple tumor-related peptides in a single vaccine has also become another approach in treating GBM. In 2012, Dutoit et al. used liquid chromatography-mass spectrometry to identify over 3000 peptides specifically expressed in HLA-A*02-positive GBM. From this pool of peptides, 11  were selected and used in the creation of the IMA950 . Forty-fHeat shock proteins (HSP) can also be utilized in peptide-based vaccines. Heat shock proteins function to control the degradation of misfolded proteins along with modulation protein aggregation in response to cellular stress. HSP70 and HSP96 are two heat shock proteins that have been found to elicit a pro-inflammatory response to GBM tumor-associated antigens (TAAs) . Clinica+ response utilizing an IFNγ enzyme-linked assay. In addition to the strong immunologic response, the vaccines proved to be well tolerated. Consequently, a phase Ib study was conducted with eight patients that were immunized with personalized neoantigen vaccines [Neoantigens are proteins derived from tumor-specific mutations that arise in protein coding and are also attractive candidates for peptide vaccine development. These neoantigens have been shown to generate a robust immune response and can function to facilitate tumor rejection ,71,72. Gvaccines . Two of Streptococcus pyogenes). This study also included a subset of patients who received intratumoral administration of the DCV via an Ommaya reservoir in addition to the standard intradermal injections. This study demonstrated the safety of DCV with no observed adverse events or radiographic evidence of autoimmune reactions. In addition to a statistically significant median OS seen in the treatment group (480 days vs. 400 days), there was an increased T-cell reactivity to tumor lysate observed post-vaccination [Dendritic cells (DCs) are antigen-presenting cells (APCs) that serve as a vital connection between innate and adaptive immunity. They are found in nearly every tissue and are known to be potent stimulators of T- and B-cells . Consequcination . Fadul ecination . ®-L, an autologous tumor lysate-pulsed DCV, showed great potential for this vaccination strategy when combined with standard therapy for a newly diagnosed GBM [n = 100) with a median OS of 40.5 months, which will be further analyzed. However, the study did not provide the IDH status of these patients. The adverse events with DCVax®-L were comparable to standard therapy alone. Final results from further analyses and follow-up have not yet been published. ICT-107 is a patient-specific DC-based immunotherapy for newly diagnosed GBM patients. This immunotherapy utilizes TAAs present on GBM cells to create six synthetic peptides that are then pulsed with the patient’s DCs. In 2013, ICT-107 was studied in a double-blind, placebo-controlled phase II trial to evaluate its safety and efficacy when administered in conjunction with the Stupp protocol for patients with newly diagnosed GBM . This trosed GBM . BlindedHuman umbilical vein endothelial cell (HUVEC) vaccines are less commonly investigated for the treatment of GBM. It is believed that HUVEC antigens elicit cellular and humoral immune responses that are antiangiogenic; thus, inhibiting tumor growth ,88,89. TSeveral studies have been able to establish that Cytomegalovirus (CMV) proteins and are expressed in over 90% of GBM tumors ,96,97. FVocimagene amiretrorepvec (Toca 511), a retroviral virus vector encoding cytosine deaminase, demonstrated a durable response rate of 21.7% in addition to a tolerable safety profile when compared to the standard of care in a newly diagnosed GBM . In 2015Cytokines are secretory molecules that help facilitate communication for the innate and adaptive immune systems. Interferons (IFN) and interleukins (IL) represent two important types of cytokines that are capable of provoking antitumor effects ,106. IL-Pseudomonas aeruginosa exotoxin A [IL-13 shares the same receptor as IL-4 and was used to create IL-13-PE38QQR, a recombinant protein vaccine composed of IL-13 and otoxin A . Althougotoxin A . Two phaotoxin A . Interesotoxin A . Additiootoxin A .Chimeric antigen receptor (CAR) T-cell therapy utilizes specially engineered immune cells to target malignancies and is effective in treating certain hematologic malignancies . This trAnother widely investigated target is IL-13 receptor variants, as they have been previously shown to have increased expression in adult glioma cells ,125. NorThe IL-13/STAT6 pathway is important in the transcription initiation of various downstream genes, including genes important for immune function ,131. AltHuman epidermal growth factor receptor 2 (HER2) is another TAA that is expressed in roughly 80% of GBMs ,135. TheHedge et al. aimed to establish the utility of a bispecific CAR molecule in improving the antitumor activity of T-cells . The autIn Sweden, a randomized phase II multicenter trial was conducted in 2015 to evaluate the efficacy and safety of immunotherapy called ALECSAT (Autologous Lymphoid Effector Cells Specific Against Tumor Cells) . ALECSATCytokine-induced killer (CIK) cells are a population of T-cells that have also been able to co-express natural killer (NK) cell surface molecules such as CD56 . To creaGBM presents unique challenges when approaching treatment from an immunotherapeutic angle. GBM is largely immunosuppressive to the systemic immune system as well as to neighboring cells alike . This laOne chemoattractant that has been studied is CX3CL1 which binds to the CX3CR1, a receptor found on a majority of microglia as well as some tumor-associated macrophages . Once acAnother important component of the tumor microenvironment is the endothelial cells of the vasculature surrounding the tumor. Through their interactions with the microenvironment, these cells contribute to poor outcomes seen in patients with GBM. In 2010, Ricci-Vitiani et al. showed that 20–90% of endothelial cells making up GBM-associated vasculature had the same mutations as the GBM cells themselves . AnotherT-cell sequestration is another unique challenge that arises in the setting of GBM. It has been shown that tumors in the CNS, specifically intracranial tumors, can cause extensive sequestration of immunocompetent cells in the bone marrow . FurtherFinally, another major challenge in treating GBM is the genetic heterogeneity these tumors display. This genetic heterogeneity can also be seen within individual tumors, which makes creating treatment plans based on a single biopsy extremely difficult ,195,196.


We consider the problem of the efficient transmit antenna subset (TAS) selection for maximizing the signal-to-interference-plus-noise ratio (SINR) of multiuser space–time line code (MU–STLC) systems. The exhaustive search for optimal TAS selection is impractical since the total number of transmit antennas increases. We propose two efficient TAS selection schemes based on the Woodbury formula. The first is to incrementally select  Multiple-input multiple-output (MIMO) transmission techniques have been employed as an integral part of present-day communication systems to improve the overall radio link capacity and reliability ,2,3,4. SRecently, a space–time line code (STLC) in  was presIn the basic STLC scheme, multiple transmit antennas are not required at the transmitter. In case multiple transmit antennas are present, STLC benefits from additional diversity gain and array gain. In , a new mction in  does notction in . Howeverction in , has beeAntenna subset selection at the transmitter and/or receiver has been researched extensively in many kinds of MIMO systems ,23,24,25In this paper, two efficient TAS selection schemes that have a better tradeoff between transmission performance and computational complexity are proposed for MU–STLC by exploiting incremental and decremental strategies, respectively, combined with the Woodbury formula. First, the Woodbury formula is utilized to reduce significantly the complexity of the conventional greedy TAS selection algorithm proposed in . Second,The effective TAS selection algorithms based on the incremental and decremental methods combined with the Woodbury formula have been designed for the MU–STLC systems;The computational complexity of the proposed TAS selection algorithms is analyzed and compared to the optimal one and the previous TAS selection scheme of . The comThe asymptotic received SINR loss is analytically provided and verified by simulation results.The main contributions of this study are summarized as follows:The rest of the paper is organized as follows. The system model of MU–STLC with TAS selection is described in k-th column vector of a matrix k-th column vector in a matrix Notations, we use lower-case and upper-case boldface letters for vectors and matrices, respectively. Superscripts t-th transmitted symbol of the k-th user, with We consider a downlink for STLC ,14,15. Tn-th receive antenna of the k-th user at time t. m-th transmit antenna and all users, which is static for The received signals with TAS selection are then represented asFor the MU–STLC decoding, the received signal matrix of (3) is re-expressed in a linear form as (4)r≜[r1By the simple STLC combining procedure at the receiver described in , the mulIn this section, we first present previous optimal and suboptimal greedy TAS selection algorithms for the MMSE-precoded MU–STLC systems. Then, the popular Woodbury formula is exploited to obtain a suboptimal incremental SNR-based TAS selection method with more reduced complexity. Furthermore, we propose a decremental TAS selection algorithm based on ZF and MMSE criteria. Finally, an efficient algorithm for decremental TAS selection is developed by using the Woodbury formula.n-th enumeration of the set of all available TASs. Here, It is easily shown that maximizing the received SINR of the MMSE-precoded MU–STLC systems is equivalent to maximizing the term ribed as .(16)SopIt should be pointed out that in the ZF precoding case, the previous works of ,25 use tented in ,25 are uthose in ,25. Furtthose in ,18,23, aObviously, the exhaustive search algorithm to solve (16) requires posed in .Algorithm 1 SINR-greedy-based TAS selection algorithm.In the MMSE-precoded MU–STLC systems, the received SNR can be used as the design criterion for the proposed incremental TAS selection optimization and readily derived from (8), (10), and (12) asTo significantly reduce the complexity of Algorithm 1, an SNR-based efficient incremental TAS selection algorithm can be developed by using the popular Woodbury formula . The firTo reduce the computational complexity further, we adopt the Woodbury formula  written Then, q-th column vector of the updated channel matrix Based on the above analysis, the procedure of the proposed SNR-based incremental TAS selection algorithm can be summarized in Algorithm 2. As an initial one of the matrix Algorithm 2 SNR-based efficient incremental TAS selection algorithm.In the ZF-precoded MU–STLC systems, the received SNR of (17) can be also employed as a design criterion for the proposed decremental TAS selection optimization. In order to see how TAS selection affects the SNR, let Thus, it is easily shown that Then, according to the Woodbury formula  written Using (27), Since If The idea of the proposed TAS selection algorithms with lower complexity is to construct a TAS by removing one by one with a decremental manner from the full channel matrix Algorithm 3SNR-based decremental TAS selection algorithm.To reduce the complexity of Algorithm 3 further, a ZF-based efficient decremental TAS selection algorithm summarized in Algorithm 4 can be developed by using (27). The first step starts with a full channel matrix and removes one transmit antenna in each decremental step. After taking In Algorithm 4, the computation of Algorithm 4 Proposed ZF-based efficient decremental TAS selection algorithm.In the MMSE-precoded MU–STLC systems, the mean square error (MSE) criterion can be adopted for the proposed efficient decremental TAS selection. For a channel matrix rived in  for MMSESimilar to the ZF-precoded MU–STLC systems, we want to see how TAS selection affects the MSE. By denoting Since Then, the optimal TAS selection algorithm based on the MSE criterion for the MMSE-precoded MU–STLC system can be formulated as .On the other hand, the received SINR penalty in MMSE-precoded MU–STLC systems can be defined asgiven as .(48)γS′The asymptotic received SINR penalty for large values of SNR in the MMSE- precoded MU–STLC systems can be obtained asFor complexity analysis of TAS selection algorithms, we consider the number of real multiplications (RMs) and the number of real summations (RSs) ,27. GiveRecall that this work has employed an From Algorithm 1, the computational complexities of the SINR-greedy-based TAS selection scheme in terms of RMs and RSs, respectively, can be evaluated line by line asRM in RS in Line 1:RM in RS in RM in RS in Line 9:RS in Line 10:Thus, the overall complexities of the SINR-greedy-based TAS selection algorithm  in terms of RMs and RSs, respectively, are given asFrom Algorithm 2 with (23) in lines 6 and 7, the numbers of RMs and RSs for the proposed SNR-based efficient incremental TAS selection algorithm can be calculated asRM in RS in Line 6:RM in RS in RM in RS in RM in RS in RM in RS in RS in RS in Line 7:Thus, the overall computational complexities of the proposed SNR-based incremental TAS selection algorithm  are given byFrom Algorithm 4 with (46) in line 3, the numbers of RMs and RSs for the proposed MMSE-based decremental TAS selection algorithm can be obtained asLine 3: RMs and RSs can be computed in a similar manner used in line 9 of RM in RS in Line 7:Line 8: RMs and RSs are the same as those, except for RS in Line 11: RSs are evaluated as in line 7 of Thus, the overall complexities of the proposed MMSE-based decremental TAS selection algorithm  in terms of RMs and RSs, respectively, are given asIn this work, (a)SINR-greedy-based TAS selection  (greedy)(b)Proposed SNR-based efficient incremental TAS selection ;(c)Proposed ZF-based efficient decremental TAS selection ;(d)Proposed MMSE-based efficient decremental TAS selection ;(e)Optimal ZF-based TAS selection ;(f)Optimal MMSE-based TAS selection .In this section, several TAS selection algorithms for the MU–STLC system with It should be pointed out that the linear precoded MU–STLC TAS systems with (a), (b), (d), and (f) employ MMSE precoders at the transmitter, whereas the systems based on TAS selection of (c) and (e) use ZF precoders.The BER performance of the proposed TAS selection algorithms is given in In Finally, This paper proposes incremental and decremental TAS selection algorithms with low complexity to efficiently reduce the number of RF chains for the MU–STLC systems. It is analyzed that the proposed algorithms achieve significantly reduced complexity than the existing greedy algorithm for the MU–STLC systems. Thus, they achieve a better tradeoff between BER performance and computational complexity for large antenna dimensions. The proposed MMSE decremental TAS selection algorithm obtains better BER performance than the existing greedy algorithm for the MU–STLC systems with relatively low antenna dimensions. Its BER performance is close to that achieved by exhaustive search-based optimal MMSE-based TAS selection algorithm for the


TUBB3, TRIM69, ZNFX1, VAV1, KCNN2, VGLL3, AK7, ARMC4, LRRC1, and CRIP1) in the occurrence and development of sarcoma. Multivariate survival model analyses were also performed, and validated that a model using these ten genes provided good classifications for predicting patient outcomes. The present study has increased our understanding of AS events in sarcoma, and the gene-based model using AS-related events may serve as a potential predictor to determine the survival of sarcoma patients.Sarcoma is a rare malignancy with unfavorable prognoses. Accumulating evidence indicates that aberrant alternative splicing (AS) events are generally involved in cancer pathogenesis. The aim of this study was to identify the prognostic value of AS-related survival genes as potential biomarkers, and highlight the functional roles of AS events in sarcoma. RNA-sequencing and AS-event datasets were downloaded from The Cancer Genome Atlas (TCGA) sarcoma cohort and TCGA SpliceSeq, respectively. Survival-related AS events were further assessed using a univariate analysis. A multivariate Cox regression analysis was also performed to establish a survival-gene signature to predict patient survival, and the area-under-the-curve method was used to evaluate prognostic reliability. KOBAS 3.0 and Cytoscape were used to functionally annotate AS-related genes and to assess their network interactions. We detected 9674 AS events in 40,184 genes from 236 sarcoma samples, and the 15 most significant genes were then used to construct a survival regression model. We further validated the involvement of ten potential survival-related genes ( Sarcomas account for 1–3% of all malignancies and estimates suggest that approximately 15,610 new cases, and 6480 deaths, occur every year in the United States2. Sarcoma is often characterized by being occult, being difficult to diagnose early, having early and distant metastases, and having an overall 5-year survival rate of less than 15% for advanced-stage disease3. Despite the therapeutic advances being made, the heterogeneity of sarcomas makes them difficult to diagnose and their treatments complex and multidisciplinary. Therefore, a more in-depth understanding of sarcoma oncogenesis is essential to elucidate the underlying oncogenic mechanisms and to identify novel diagnostic and therapeutic biomarkers for sarcoma patients.Sarcomas are rare and recalcitrant malignant mesenchymal tumors represented by more than 100 subtypes with different prognoses4. Alternative splicing (AS) is a ubiquitous and important regulatory step in gene expression, enabling a fixed number of genes to generate a large variety of mature mRNAs. This increased transcript variety is also responsible for expanding the diversity of the transcriptome and the proteome. AS also has the potential to regulate gene expression, and therefore impact important molecular events for cellular differentiation and cell-type specific functions5. In the human genome, AS has been shown to play a vital role in the regulation of multiple molecular mechanisms and biological functions6. Aberrant AS events results in the inactivation of tumor-suppressing genes, promotion of angiogenesis, acceleration of proliferation, and inhibition of apoptosis7. Prominent in cancer, AS has now become a potential target for cancer therapeutics8. AS events are post-transcriptional processes that modulate gene expression, and are responsible for the increased proteomic diversity seen in a variety of cancers activities9. Aberrant AS events may also be relevant for explaining functional transformations in cancers10, often referred to as the "hallmarks of cancer" for prostate, ovarian, breast, colon, bladder, and lung cancer, among others17. AS events have also been reported to be involved in the regulation of apoptosis and autophagy genes19, tumor responses to chemotherapy, the orchestration of cancer stem-cell biology, and in epithelial-to-mesenchymal tumor transitions21. The regulators of RNA AS have the potential to become novel oncoproteins, contributing to dysregulation by modulating RNA isoforms in cancer-related pathways, and may be both biomarkers and targets for sarcoma diagnostics, prognostics, and treatments.Accumulating evidence has demonstrated that aberrant regulation of gene expression is involved in sarcoma initiation and tumor progressionThe Cancer Genome Atlas (TCGA) database contains a large number of gene profiles that can be used to investigate novel AS-related gene expression and prognosis data for cancer. In this study, we systematically analyzed AS events and constructed an AS-based gene model based on the sarcoma database in TCGA.AS-event profiles were identified and analyzed in-depth from 236 sarcoma samples from the TCGA sarcoma cohort. We identified the seven AS patterns  listed in Fig. To detect AS-event gene frequencies in sarcoma and survival, we integrated the clinical survival data from sarcoma patients. Using a univariate survival analysis, we obtained 2974 significant associations between prognoses and AS events Fig. C, and 23To determine the prognoses associated with the seven different AS-event subtypes, we calculated the relationships between AS subtypes and the landscape for overall survival genes. The seven AS-event subtypes were closely associated with overall survival prognoses Fig. A, and anTo determine possible prognostic factors based on sarcoma AS events, we selected the 15 most significant genes to construct a survival regression model using area-under-the-curve (AUC) values. The results demonstrated that the seven AS-event subtypes all had high AUC values. For overall survival, the AUC values showed that AP (AUC = 0.902) was highly accurate and that AD (AUC = 0.879) and AT (AUC = 0.824) were well-suited for prognostic predictions. The other subtypes  also had predictive AUC values , indicating that the variable-splicing events of most genes were significantly related to their expression levels.To determine any correlations between gene expression and the prognoses for these variable-splicing events, that were significantly related to patient outcomes, we utilized a univariate survival analysis based on TCGA RNA-seq gene expression data. From this data, we used the 267 survival-related AS genes that were correlated with patient prognoses, and then Pearson correlations were performed to assess significance. We found that 149 (55.81%) of these genes were significantly related to variable-splicing . To understand the relationship between potential hub genes and survival status, the risk scores for these 21 genes were calculated  closely associated with the occurrence and development of sarcoma. TUBB3, which codes for a microtubule protein, was overexpressed and linked to poor prognoses in a variety of cancers30. The function of TRIM69, a member of the tripartite motif (TRIM) family, has been reported to inhibit virus replication through a transcription-inhibition mechanism that prevented the synthesis of viral messenger RNAs31. ZNFX1, a novel lncRNA that has been shown to regulate cell proliferation, the cell cycle, cell migration, and cell invasion, may be a promising biomarker to predict poor prognoses in many cancers34. The ten hub genes were also involved with cancer initiation and progression, correlating with progression35. VAV1 has been reported to play a crucial role in the progression of human cancer, and AK7 expression has been positively correlated with malignant-cell proliferation in both acute lymphoblastic leukemia and Burkitt's B cell lymphoma36. ARMC4, an axonemal protein necessary for proper targeting, has also been identified among the novel genes associated with tumorigenesis in colorectal cancer37. LRRC1,a putative cell-polarity regulator, was significantly upregulated and considered to be a potential oncogene in hepatocellular carcinoma38. CRIP1 has been reported to be overexpressed in many cancer tissues and is considered to be an oncogene in tumor development and progression39.In this study we also identified ten prognosis-related genes  compiled from TCGA. Data from a total of 261 samples were collected from the TCGA database (https://cancergenome.nih.gov/), including two normal tissue samples, and the RNA-seq gene expression profiles were from sarcomas and para-cancerous tissues. All represented patients had well-documented clinical information and follow-up data. The gene expression data in fragments per kilobase of exon model per million reads mapped (FPKM) were transformed into transcripts per million (TPM) values.RNA-seq data from sarcoma AS events were downloaded from the SpliceSeq database , mutually exclusive exons (ME), retained intron (RI), alternate promoter (AP), alternate terminator (AT), alternate donor site (AD), and alternate acceptor site (AA).http://cran.r-project.org/package=survival), and the level of significance was set at P < 0.05.Analyses of patient survival data were made using the survival package in R software (http://string-db.org/), and applied a threshold score > 0.4. Data visualization was performed using Cytoscape (https://cytoscape.org/).For the analysis of gene-network interactions, we used the STRING database (https://kmplot.com/).We performed a multivariate analysis of the gene expression data using the Cox proportional hazard-regression model. We identified the ten AS-related genes that demonstrated the most significant expression-profile changes, and then used these hub genes to create a prognostic model and for survival analyses. In addition, we determined the correlations between the expression profiles of these ten hub genes and overall patient survival based on Kaplan–Meier plots , a web-based tool for gene/protein functional annotation and pathway-enrichment analysis.To determine the functions of the prognostic genes that were significantly related to AS events, we used KOBAS 3.0 (Characteristic genes were selected as being significantly prognostic with Pearson correlation coefficients of more than 0.5 or less than − 0.5. To construct our prognostic model, we used these prognostic genes and the frequencies of AS events, to develop a sarcoma prognostic index.To determine correlations between levels of gene transcription and variable-splicing prognoses, we used a univariate analysis of AS-sequence profiles using TCGA RNA-seq data for associated genes to determine the impact of AS events on sarcoma prognosis.