The efficiency of conventional screening programs to identify early-stage malignancies can be limited by the low number of cancers recommended for screening as well as the high cumulative false-positive rate, and associated iatrogenic burden, resulting from repeated multimodal testing. The opportunity to use minimally invasive liquid biopsy testing to screen asymptomatic individuals at-risk for multiple cancers simultaneously could benefit from the aggregated diseases prevalence and a fixed specificity. Increasing both latter parameters is paramount to mediate high positive predictive value—a useful metric to evaluate a screening test accuracy and its potential harm-benefit. Thus, the use of a single test for multi-cancer early detection (stMCED) has emerged as an appealing strategy for increasing early cancer detection rate efficiency and benefit population health. A recent flurry of these stMCED technologies have been reported for clinical potential; however, their development is facing unique challenges to effectively improve clinical cost–benefit. One promising avenue is the analysis of circulating tumour DNA (ctDNA) for detecting DNA methylation biomarker fingerprints of malignancies—a hallmark of disease aetiology and progression holding the potential to be tissue- and cancer-type specific. Utilizing panels of epigenetic biomarkers could potentially help to detect earlier stages of malignancies as well as identify a tumour of origin from blood testing, useful information for follow-up clinical decision making and subsequent patient care improvement. Overall, this review collates the latest and most promising stMCED methodologies, summarizes their clinical performances, and discusses the specific requirements multi-cancer tests should meet to be successfully implemented into screening guidelines. Detecting cancer at an early stage , when primary tumours are still localized and have not spread to the surrounding tissues, remains the best strategy for successful treatment and increased overall survival rate ,2,3,4. TOne of the most promising avenues to early-stage disease detection is liquid biopsy testing from blood, and to a lesser extent, urine, as these body fluids are known to carry specific cancer biomolecules  that directly originate from malignant tissues. These biomarkers are released by cancer cells through various mechanisms and have been reported to harbour specific signatures that could reflect tumour burden, stage, or location, a precious source of clinical information for cancer diagnosis as well as treatment monitoring ,9,10,11.Two different strategies are currently available for interrogating ctDNA from blood in biomarker discovery and cancer diagnostic development. The most established method consists of using next-generation sequencing analysis to probe for specific genetic abnormalities  associated with cancer which quantitative genotypic information of tumour burden provides based on variant allele frequency (VAF) ,13,14, aWith the recent advances in molecular technologies, the last decade has encountered a true revolution in genomic and epigenetic profiling methods and an exhaustive number of these informative regions have been reported for clinical utility ,16,17,18Individuals with early-stage malignancy are usually asymptomatic and remain untested; it is only with the presentation of symptoms that diagnosis occurs, a situation often associated with a more advanced stage of the disease and poor prognosis. Faced with this, an ideal approach for increasing early detection rate would appear to be a clinical recommendation to perform a general cancer test on an annual basis for all asymptomatic individuals in the general population. However, to be implemented for general screening of healthy individuals, a test would presumably need to achieve a maximal specificity of 100% to limit the false positive rate to 0% and ensure adequate clinical risk–benefit. Indeed, every false-positive result would misguide any patients towards further clinical testing, with concomitant negative impacts on patient mental health and healthcare system burden. For instance, if 1 billion tests were to be performed using a diagnostic test with a specificity as high as 99.9%, it would still result in 1 million individuals incorrectly classified as having disease, all of whom would have to endure an unnecessary and expensive diagnostic odyssey. Given this false-positive problem, screening the general population annually seems unrealistic and may not be a practical strategy to improve early cancer detection rate.As an alternative, conventional guidelines recommend cancer screening for at-risk individuals  mostly targeting age-restricted populations . For insCroswell et al. conducted a randomised controlled trial to evaluate the incidence of false-positive results in repeated multimodal cancer screening [As detailed above, the current screening paradigm relies on methods that have been developed to interrogate one specific organ at a time, while individuals may undergo screening for more than a single disease. The major drawback of such multimodal screening programs is that the cumulative risk for an individual to obtain a false positive result will inevitably increase with the number of screening tests performed. creening . The stuIn addition, a conceptual limitation of the current guidelines to effectively increase early cancer detection rate is that screening is only recommended for a handful of cancer . This stMoreover, some of the conventional screening methods such as optical colonoscopy or cervical cytology testing can involve invasive procedures that could cause discomfort and, in some cases, complications ,30. OtheThe technological performances of diagnostic assays are generally reported in terms of specificity  and sensitivity  as paired indicators. Integrating both parameters into a single indicator of diagnostic performance could help compare the effectiveness of competing tests and facilitate decision making. For instance, the Diagnostic Odds Ratio (DOR) can be utilized as such a single indicator and is defined as the odds of disease in positive testing over the odds of disease in negative testing . HoweverIn summary, the limited number of cancer types targeted by guidelines-recommended screening as well as conventional multimodal testing programs accepting relatively low specificity are the major limitations to efficiently improving early cancer detection rate. One promising strategy to potentially address these limitations and yield higher PPV is implementing a high specificity blood-based test for screening multiple cancer types simultaneously.While individuals may be identified as at-risk for a particular cancer type , their combined risk of developing any other cancer  is substantially greater than the individual risk of cancer they are being tested for ,4. It isAlthough cancer is mainly considered to be a disease driven by genetic mutations, epigenetic alterations are also a critical factor for the onset of malignant diseases and tumours development. DNA methylation at CpG dinucleotides—enzymatically mediated by DNA Methyltransferase—is a global epigenetic mark used to regulate gene expression and signalling pathways activity to control diverse cellular functions. The subsequent regions of the genome that are demarked for transcriptional activation or silencing are of critical importance to define the functionality of a cell and maintain proper homeostasis . As suchDuring cancer-related methylome reprogramming, two major epigenetic abnormalities occur across the genome—DNA hypermethylation and hypomethylation. DNA hypermethylation tends to cluster at regulatory regions enriched with CpG islands which are normally unmethylated and function to control the activity of anticancer mechanisms but become silenced upon hypermethylation. Notably, the ability to modulate the functional state of such promoter regions acts as an alternative to somatic mutations to block the activity of tumour suppressors and DNA repair genes, thereby promoting cancer progression ,48,49. CThe potential outlined above of clinical epigenetics for early disease detection has resulted in a flurry of in-vitro diagnostic (IVD) tests based on DNA methylation analysis of ctDNA, with the majority of these tests targeting panels of hypermethylated CpGs associated with specific oncogenic genes, typically for the detection of a single specific cancer type ,53,54. FAlthough these ctDNA methylation-based IVD assays relying on minimally invasive analysis have significantly improved the standard of care methods and highlight the potential of cancer epigenetics, they are still designed to target one specific type of cancer and thus do not fully address the aforementioned limitations. One potential avenue is to exploit artificial intelligence methods to analyse large datasets and build more comprehensive DNA methylation panels to predict specific cancer types, and eventually combining them for the development of a single test for multi-cancer early detection. However, one challenge associated with stMCED is the ability to correctly identify the tumour of origin after a blood-test returns positive. With that regard, acquired DNA methylation state can be tissue-specific and maintained during neoplastic transformation, creating epiclone signatures that could allow tumour of origin identification ,59. ThisMethodologies for sensitive and accurate detection of multiple cancer types using a single assay are emerging as a promising paradigm for potentially increasing early cancer detection rate and improved harm-benefit tradeoff when screening asymptomatic individuals in the ageing and at-risk populations. To be successfully implemented into screening programs and effectively improve health impact while minimizing the associated risk, stMCED would need to meet the following specific criteria . (1) TheThe recent advances in sequencing and PCR technologies have certainly allowed the development of powerful molecular assays enabling high throughput and large-scale analysis of the human genome. With the help of bioinformatics, it is now possible to analyse these extensive genomic (or epigenomic) datasets to decipher combinatorial biomarkers highly specific to different cancer types. These computational methodologies have opened new avenues for the discovery and the generation of larger, more comprehensive and more performant biomarkers panels suitable for stMCED. Here, we discuss the most promising blood-based diagnostic assays utilizing ctDNA analysis for the detection and potential identification of multiple cancer types at an early stage of disease and compare the performance of methylation-based and other technologies . In addition, the methodology is still at an initial development stage and the authors have not published pieces of evidence yet about the ability of the platform to accurately predict the tumour of origin of a sample that tested positive. Although larger datasets are needed to improve the classifiers’ performance and independent cohort for further validation of the models, the interrogation of genomic variants only may limit the possibilities of identifying specific cancer given the heterogeneous nature of somatic mutations.Cohen et al. [CancerSEEK is one promising blood-based test developed to detect and locate the presence of eight different types of cancers  using an innovative multi analytes approach—targeting both genetic and protein biomarkers . The firn et al.  have desPanSEER is a recent promising blood-based cancer screening test relying on a large panel of ctDNA-methylation biomarkers for the early detection of five major cancer types , up to four years before conventional diagnostic programs . The assOne appealing aspect of the PanSEER study for evaluating early cancer detection was the opportunity to retrospectively interrogate blood samples from a large longitudinal cohort including individuals who were initially asymptomatic  and who later developed a disease that was detected by conventional diagnosis within four years . The analyzed cohort included 191 of these ‘pre-diagnosis’ patients , 414 participants that remained healthy, and an additional set of 223 ‘post diagnosis’ patients who already had cancer . Half of the samples were randomly assigned to a training set used to generate the cancer classifiers, while the rest were left out for a test set used to independently validate the final developed models. The initial training set was randomly split into two different sub-sets—one for training a cancer classifier and the other for its validation. To prevent potential bias and of using a single training set for fitting the classifier and subsequent misclassification, this process was repeated 1000 times to generate a robust and final model averaging all classifiers’ prediction score output. At a fixed specificity of 95%, this final model achieved a sensitivity of 88.2% in the post-diagnosis group and 91.4% in the pre-diagnosis group using the training set samples. At a fixed specificity of 96%, the analysis of the independent left-aside test set yielded an overall sensitivity of 87.6% (AUC = 0.97) in the post-diagnosis group, and 94.9% (AUC = 0.99) in the pre-diagnosis, together with consistent sensitivity for patients diagnosed with a disease from 1 to 4 years later. Importantly, the authors report similar performances when the model analysed either early and late-stage samples across the entire cohort , pancreatic cancer , lung cancer , and healthy controls (n = 62), resulting in high mean AUROC value to classify each cancer versus all-others . Most importantly, the classifiers were yielding similar prediction accuracy when comparing early stage versus late-stage samples for PDAC (0.914 vs. 0.92) and LUC (0.975 vs. 0.966). Together, the cfMeDIP-seq method has been proved to be efficient to retrieve large scale methylation signatures from ctDNA that are highly specific tumour types when carefully selected by machine learning models.  from blood and urine, including early-stage samples . This stAn additional separate study was conducted to evaluate the performance of cfMeDIP-seq method to identify highly specific plasma methylation signatures to detect and discriminate intracranial tumours . Using tSuch body of evidence clearly demonstrates the indisputable properties of DNA-methylation to be organ type and sub-type specific, and its subsequent power to predict tumour of origin from blood ctDNA when applying appropriate computational models. Although no detailed data have been found regarding the sensitivity of the methods at a specific specificity to detect cancers, the reported AUROC to predict cancer and accurately identify the tumour of origin from early-stage samples provides evidence of the potential of cfMeDIP-seq to be implemented as an MECD.® is another recent technology  harnessing the power of methylation signatures for early-stage detection of specific cancer from a blood sample. The platform has also been developed using next-generation sequencing data and bioinformatics to identify specific hypermethylated gene targets and build proprietary methylation-based biomarker panels [® studies is that each patient cohort was designed to include benign tumours in addition to other cancer types and healthy control samples, which is an important factor to better represent a population spectrum and provide a more accurate assessment of how the test will perform in real settings.IvyGener panels . The tesr panels . More prLiu et al. [In that technological space, the biotech company GRAIL represents a significant shift with their ambitious circulating cell-free genome atlas (CCGA) study, a large-scale population investigation for cancer cfDNA signatures discovery, to develop a blood-based cfDNA multi cancer early detection assay. In a first sub-study, u et al.  conducten = 359), the test was able to predict the tumour of origin with more than 89% accuracy (321/359).In the following CCGA sub-study, these previous WGBS findings and publicly available methylation array data have been used to develop a cfDNA bisulfite sequencing assay targeting a panel of 103,456 informative methylation regions and build classifiers for cancer detection and tissue of origin prediction . The claThis developed targeted methylation-based assay was further optimized and independently validated in a third and final clinical sub-study using a large cohort of 4077 samples  . The repCompared to the other stMCED platforms, GRAIL is certainly the most powerful and which has been thoroughly validated by large cohorts of participants. Even though the overall sensitivity is similar or lower than the other techniques discussed herein (in particular for early disease stages), the ability to target that many cancer types simultaneously with a false positive rate of only 0.7% would yield the highest PPV compared to other methods targeting fewer diseases with reduced specificity. Indeed, a screening test would significantly benefit from a higher aggregated prevalence—by increasing the number of targeted organs—with moderate sensitivity, rather than favouring sensitivity with a reduced number of interrogated cancers and specificity. The additional ability to predict the tumour of origin with good accuracy is certainly of great additional value for patient health and finances. However, that package of benefits is only possible at an elevated price because a very high number of genomic regions need to be interrogated through sequencing technology, which may be a limit for the uptake of the test by the targeted population.n = 45) from advanced colorectal and breast cancer (n = 100) samples with relatively good performance (AUROC = 0.887). However, further development is still required to assess the potential of Methylscape to detect earlier stages of diseases and independent validations including a larger panel of cancer types across multiple cancer stages are still needed to be done.Despite being highly robust and powerful, all the methodologies reported above entirely rely on PCR and sequencing technologies, involving relatively expensive equipment and well-trained operators, thereby limiting their access in resource-poor countries and remote areas. Knowing that disease screening is only feasible with technologies that could be implemented and sustained in low-resource settings, simpler and cheaper screening methods are still needed for cancer diagnostic intervention beyond the boundaries of the first world . In thatAlthough Methylscape showed lower cancer detection accuracy than the other sequencing-based assay described above, its simple methodology enables reduction of sample preparation process to the bare minimum  allowing for putting forward a very simple and yet efficient technology at a significantly reduced cost. Thus, Methylscape could be implemented using portable equipment and could find great opportunities in low-resource settings as a “quick and cheap” first-line screening technology for cancer detection.Conventional multimodal screening programs are mainly limited by the low number of cancers recommended for screening as well as the high cumulative false-positive rate and associated harms resulting from repeated testing. The possibility to use minimally invasive blood tests to screen asymptomatic individuals at-risk for multiple cancer types simultaneously would benefit from a fixed specificity and the aggregated diseases prevalence, both parameters increasing the positive predictive value of the test and its efficiency. As such, stMCED technologies are now emerging as a promising paradigm for increasing earlier disease detection rate with better harm–benefit trade-off and potentially improving population health. However, the development of these technologies must show a positive clinical cost–benefit to allow potential implementation into current screening programs. With this regard, the risk–benefit analysis of these tests should be systematically performed based on diagnostic performances to evaluate their net clinical impact on the healthcare system and patient’s health, management, and finances. For successful translation, the net benefit of any of these tests should outweigh the total risks associated with its use. For instance, a hypothetic low-cost test sensitive enough to detect localized diseases and potentially improve patient survival outcome, but showing a relatively high false-positive rate and/or the inability to identify the tumour of origin would probably remain too risky for screening settings. As such, the burdensome consequences resulting from inaccurate testing would still outweigh the potential health benefit.While the legitimate clinical utility of DNA-methylation compared to genetic alteration for accurate cancer diagnostic has been debated in the scientific community, there is now unprecedented evidence tipping the balance in favour of epigenetic biomarkers. One important and underappreciated aspect of cfDNA-based liquid biopsy testing is the relationship between the reported sensitivity of these tests and the amount of input DNA required to achieve it. For example, one complete copy of the human genome is equivalent to approximately 3 pg of DNA , and an Nonetheless, to correctly infer the clinical cost–benefit of a test, its performances must be thoroughly validated by independent clinical studies. Designing robust studies that faithfully reflect the targeted population can be challenging when investigating early stage of malignancies as diseases prevalence are low and a very large number of samples should be included for statistical significance. In that line, case-control studies often fail to accurately represent the broad spectrum of individuals within risk populations as they usually include retrospective samples from either cancerous or non-cancerous patients and often omit to include other cancer-like patients such as benign neoplasms or inflammatory associated samples. This could raise concern as DNA methylation mechanisms have been reported to also be triggered during such cancer-like responses which could lead to false assessment of a diagnostic performance .Altogether, the overall capabilities of these stMCED technologies are strongly dependent on the selected biomarker panels and richness of patients’ cohorts used for generating the input data to train the core machine learning classifiers. The diagnostic power of these computational methodologies is believed to significantly improve with growing datasets and could potentially achieve optimal performance by combining genetic and epigenetic biomarker panels to eventually satisfy the clinical cost–benefit required for successful implementation. Although these stMCED methodologies are reporting promising diagnostic performances, their overall sensitivities to detect early stage of cancers  are still underperforming compared to later stage detection. Research in the field should endeavour towards the development of new panels or technologies of early-stage biomarkers—with the capabilities to determine whether a neoplasm tissue will transform into an aggressive tumour or remain benign—to effectively increase earlier detection of malignant diseases and facilitate improved treatment opportunities and clinical outcome of patients.The cancer diagnostic tests reviewed in this article have been selected from the literature after a digital search on Google Scholar for the following criteria: (1) published online within the last four years (from 2018 onwards), (2) using circulating tumour DNA analysis from liquid biopsy testing, (3) focusing on the detection of multiple cancer types, (4) reporting on the ability to detect early stage of malignant diseases, and (5) using DNA methylation biomarkers for cancer detection. In addition, two distinct methodologies not utilizing DNA methylation biomarkers, but somatic mutation analysis, have also been included in this review to better contrast the performance of diagnostic tests in this space as we believe this information is of value to readers.S. Tenny and M.R. Hoffman [In-silico modelling of a diagnostic test PPV in relation to different sensitivity, specificity, and disease prevalence parameters was performed using the following equation reported by  Hoffman :PPV=prev Prism 8 .®, cfMeDIP-sequ, and Methylscape were excluded. The disease prevalence data used to estimate the PPV have been obtained from Cancer Australia’s National Cancer Control Indicators (NCCI) website [When possible, the PPV associated with the methodologies discussed in this review was evaluated using Equation (1), and data are shown in  website  and are


Resistance exercise has been shown to improve muscle health in older adults and is recommended as a front-line treatment for many health conditions, including sarcopenia and frailty. However, despite considerable research detailing the potential benefits of resistance exercise programmes, little is known about how older adults recover from individual exercise sessions. This scoping review will examine the current evidence surrounding the acute post-exercise effects of resistance exercise and the exercise recovery process in older adults to inform future research and exercise prescription guidelines for older adults.The methodological framework of Arksey and O’Malley (2005) will be applied for this scoping review. A systematic search of five online databases and the hand-searching of reference lists of identified articles will be used to identify relevant papers. Studies that aim to measure exercise-induced muscle damage or exercise recovery following a resistance exercise session in participants aged 65 years and over will be included. Qualitative and quantitative data from relevant studies will be presented in a tabular format. Results will be summarised in narrative format. Key findings will be discussed concerning resistance exercise prescription in older adults.This review will be used to direct further research surrounding the exercise recovery process from resistance exercise in older adults and will also aid in designing specific exercise prescription guidelines for an older population. Findings will be relevant to researchers, clinicians, health workers and policy-makers and disseminated through publications and presentations. Older adults may recover from resistance exercise differently, but there is currently no comprehensive literature review.This novel scoping review will collate research and map the literature surrounding recovery from resistance exercise in older adults.The review will bring together literature from both clinical and exercise science disciplines and begin to aid in designing specific exercise prescription guidelines for older populations.Resistance exercise, also known as strength training or resistance training, has been shown to be effective in improving muscle health in older adults.Despite the potential long-term benefits, performing resistance exercise may cause unfavourable short-term side effects as a result of transient fatigue and exercise-induced muscle damage. Exercise-induced muscle damage typically occurs due to unaccustomed or intense exercise. It is characterised by muscle soreness and a loss of skeletal muscle function immediately after and in the days following an exercise bout.Traditionally, resistance exercise has been performed by athletes to improve physical performance. As such, a large proportion of the literature surrounding exercise recovery and muscle damage is concentrated on younger adults. According to the theory of adaptation,The main aim of resistance exercise for older adults is maintaining muscle mass and strength. Yet, any transient decrements in physical functioning resulting from intense exercise in these individuals could hinder their ability to perform habitual activities such as climbing a flight of stairs or acutely increase their risk of falls.This scoping review will map the current evidence surrounding exercise-induced muscle damage and recovery from resistance exercise in older adults. Specifically, this review aims to establish; (a) which population groups have been studied; (b) how the exercise recovery process has been characterised; (c) what acute post-exercise effects of resistance training have been documented in older adults; (d) the time course of exercise recovery in older adults and (e) what variables (if any) have been shown to alter the exercise recovery process in this population.This review protocol will be reported in accordance with the guidance from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR).The overall aim of this review is to assess the current evidence surrounding exercise-induced muscle damage, and recovery from resistance exercise, in older adults. The research questions have been defined as follows:Which population groups have been included in current research  and what are the key characteristics of the resistance exercise undertaken ?How has recovery been characterised? What are the key outcomes (both subjective and objective) that have been measured to quantify exercise-induced muscle damage and the exercise recovery process?What are the acute post-exercise effects of resistance exercise, including physiological markers of exercise-induced muscle damage and ability to complete daily tasks, and what is the time course for these effects?Which variables have been shown to affect the extent of muscle damage and the time course of the exercise recovery process in an older population ?We define the key terms of the research questions as follows:Resistance exercise: any physical activity that produces skeletal muscle contraction(s) by using an external resistance or weight.Exercise-induced muscle damage: A temporary disturbance in the function or structure of skeletal muscles as a result of intense or unaccustomed exerciseExercise recovery: The process of resolving physiological and psychological disturbances that may occur due to performing an intense or unaccustomed exercise. This process begins once exercise has ceased.For this review, we define the period during which exercise recovery occurs immediately after and up to 7 days following the exercise session. We acknowledge that some symptoms of muscle damage may extend past this time frame after very intense exercise, but this is unlikely to be representative of exercise performed by an older population. This time frame will also allow us to ensure we are identifying studies that measure exercise recovery instead of chronic training adaptations.The following electronic databases will be searched using MeSH terms and free text: MEDLINE, Scopus, Embase, SPORTDiscus and Web of Science. In addition, reference lists of all identified articles will be screened for additional studies.The search strategy will include terms related to the population of interest  in combination with the exercise mode  and the outcomes of interest . The full search strategy is available in 10.1136/bmjsem-2021-001229.supp1Supplementary dataAll primary research articles that meet the criteria will be included in the review. Studies that contain older adults of both sexes from all races/ethnicities, settings and geographical areas will be included. We will not exclude studies that contain a younger age group in addition to older adults. Although we will not require studies to exclusively include healthy, disease-free older adults, studies that have been conducted within specific clinical populations will be excluded. We will also exclude trials where there is no ‘exercise only’ condition  and where there is, therefore, no data on the participants usual response to resistance training.Different outcomes than those stated in All eligible articles will be uploaded to Zotero 5.0, where duplicate articles will be removed. The authors will conduct the initial screening of the articles. To ensure the suitability of the selected studies for the research objectives, two reviewers (EJH and CH) will screen by title and abstract. Any excluded studies will be reviewed by a third reviewer (AG). If the eligibility of a study is not clear from the abstract, a full-text article will be obtained. Full-text screening of the subsequently selected articles will be conducted by two reviewers independently (EJH and CH). Every effort will be made to obtain full-text articles of the selected articles, including web searching, contacting the necessary authors and consultation of a university librarian. Discrepancies between reviewers will initially be sought to be rectified by discussion. In the case of no resolution, a third reviewer (AG) will be asked to determine a consensus.Data will be extracted from all eligible studies using a standardised form to chart the data developed by three reviewers . As is the nature of a scoping review, this form may need continually reviewing by the reviewers throughout the data extraction process to ensure all relevant information is gathered to address the aim of the scoping review successfully. This form aims to gather all of the relevant information surrounding the exercise recovery process in older adults. Data will be charted by one author (EJH) and checked by a second author (CH). Any disagreements will be resolved first by discussion between the two reviewers or further adjudicated by the third (AG) if a unanimous decision is not made.Information of interest will include the following:Study characteristics: year of publication, journal, aims and objectives of the study, study design, sample size, country of origin, study settingParticipant characteristics: population sampled, age , sex , training status .Resistance exercise intervention protocol .Outcome results The time frame of outcome measures Presence of any comparison groups .Key relevant findings and conclusionsA PRISMA flow diagram will be used to report the final numbers of relevant articles included in the review. Both quantitative and qualitative data from relevant studies will be presented in a tabular format, with further narrative descriptions if necessary. The study findings will be synthesised in a narrative format based on the research questions and any themes identified during data extraction. The implications of these findings and identified gaps in the literature will also be discussed in narrative form.Our key findings, alongside other relevant exercise science literature, will be discussed in relation to the prescription of resistance exercise in older adults. The review will also highlight the key areas where additional or better-quality evidence is needed before specific recommendations regarding exercise recovery in older adults can be made.There will be no patient or public involvement in our scoping review.The completed scoping review will be submitted for publication in a peer-reviewed journal and contribute to a PhD thesis. Any findings from this review will also be disseminated at appropriate conferences. Findings from this review can be used to direct further research surrounding the exercise recovery process from resistance training in older adults. Still, they may also begin to inform specific exercise prescription guidelines for an older population. Only secondary data will be used for this review, and therefore ethical approval is not required.The short-term post-exercise effects of resistance exercise are poorly understood in older adults. This scoping review will assess the current knowledge of exercise-induced muscle damage and recovery from resistance exercise in older people. Given the unique challenges that can be presented by older age, such as reduced functional capacity, ability to perform day-to-day activities and increased falls risk, this review will aim to apply its findings in a context that is relevant for older adults. It will also highlight gaps in the literature investigating how the exercise recovery process may be altered by training status or nutrition. Overall, this review will aim to bring together literature from both clinical and exercise science disciplines and begin to inform practical recommendations for implementing resistance exercise in an older population. This review can increase awareness of the varying needs of older adults in a post-exercise setting and will also provide a catalyst for interdisciplinary conversation and research aiming to establish better guidelines for exercising older adults.A potential limitation of this scoping review is that no firm conclusions may be drawn regarding best practices for prescribing resistance training in older adults. Indeed, due to a lack of rigorous quality appraisal of studies, this review is intended simply to map the extent of the literature and begin to discuss possible implications for exercise prescription.


Polypoidal choroidal vasculopathy (PCV) is a subtype of neovascular AMD (nAMD) that accounts for a significant proportion of nAMD cases worldwide, and particularly in Asia. Contemporary PCV treatment strategies have closely followed those used in typical nAMD, though there are significant gaps in knowledge on PCV management and it remains unclear if these strategies are appropriate. Current clinical trial data suggest intravitreal anti-vascular endothelial growth factor (VEGF) therapy alone or in combination with photodynamic therapy is effective in managing haemorrhage and exudation in PCV, although the optimal treatment interval, including as-needed and treat-and-extend approaches, is unclear. Newer imaging modalities, including OCT angiography and high-resolution spectral domain OCT have enabled characterisation of unique PCV biomarkers that may provide guidance on how and when treatment and re-treatment should be initiated. Treatment burden for PCV is a major focus of future therapeutic research and several newly developed anti-VEGF agents, including brolucizumab, faricimab, and new modes of drug delivery like the port delivery system, offer hope for dramatically reduced treatment burden for PCV patients. Beyond anti-VEGF therapy, recent developments in our understanding of PCV pathophysiology, in particular the role of choroidal anatomy and lipid mediators in PCV pathogenesis, offer new treatment avenues that may become clinically relevant in the future. This article explores the current management of PCV and more recent approaches to PCV treatment based on an improved understanding of this unique disease process. Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss worldwide , 2. SeveDespite these differences, current therapeutic options of PCV have largely evolved from treatments designed for typical nAMD. In this review we will discuss how the latest clinical trials in PCV, coupled with improved understanding of pathogenesis from imaging studies, have progressively contributed to the formulation of PCV-specific treatment approaches. We go on to highlight some emerging treatments that may soon play an important role in PCV management.Prior to the availability of optical coherence tomography, the PL was the main target of treatment, as this was the most obvious source of haemorrhage and exudation based on clinical examination, fluorescein angiography, and ICGA. Closure of the PL with focal laser or subsequently with verteporfin photodynamic therapy (PDT) have been widely used –15.Historically, the management of PCV with PDT was complicated by acute vision loss and massive subretinal haemorrhage . These cThe PLANET study , 22 evalResults of these therapeutic studies were also important in the evolving understanding of the nature of PCV lesions. While earlier studies emphasised the difference in the benefit of PDT in PCV compared to typical nAMD, the two lesions had been proposed to be distinct entities. With more recent studies which demonstrate that anti-VEGF therapy can be used successfully as first-line therapy in PCV and typical nAMD, the similarities of these two subtypes were increasingly appreciated. Concurrently most imaging and histopathology studies place the BNN in PCV lesions in a plane between the retinal pigment epithelium (RPE) and Bruch’s membrane. This finding further supports a conclusion that the BNN is a type 1 MNV instead of an intrachoroidal vascular channel as suggested in earlier studies based on ICGA, which did not have the benefit of depth resolution that OCT offers. There have also been some reports that PCV may uncommonly display a type 2 MNV appearance, affirming similar features to the typical nAMD subtype , 24.Recognising that the BNN component of the PCV lesion is neovascular in nature, the anti-VEGF treatment regimens in PCV have also progressively become more aligned with that in typical nAMD. A popular treatment protocol for typical nAMD is the treat and extend (T&E) regimen. Briefly, the T&E protocol dictates that patients receive three initial monthly loading doses of anti-VEGF therapy followed by progressive adjustment of the treatment interval according to anatomical and functional outcomes. This interval can be extended by weeks or months with the aim of reducing treatment burden. These regimens use disease activity markers of fluid in retinal compartments, visual acuity and presence of haemorrhage on clinical examination for retreatment decisions. While not as extensively studied, PCV patients undergoing a T&E protocol show favourable outcomes comparable to patients with typical nAMD –31. HoweIn addition to fluid, the PL within the sub-RPE vascular network is responsible for much of the exudation in PCV . A potenIn current clinical practice the management of PCV following commencement of initial therapy is guided for the most part by visual acuity, the presence of subretinal and intraretinal fluid, and the status of the PL as mentioned above. While these features have informed the outcomes of previous PCV clinical trials, there is a growing body of literature suggesting several other morphological and physiological features specific to PCV may also have value as treatment biomarkers.A sharp-peaked PED and a sub-RPE ring-like lesion on OCT have been reported to be frequently associated with and co-localise to PL on ICGA. The Asia Pacific Ophthalmic Imaging Society (APOIS) PCV workgroup has shown that OCT is a viable alternative to ICGA in assessing the presence of PL in treatment naïve eyes as well as in eyes with persistent fluid following monthly anti-VEGF loading treatment . Fig. 11 FeatureOCT angiography (OCTA), a novel imaging modality which detects blood flow, may also be able to detect flow signal within the PCV lesion , 43. SpePCV resides within the pachychoroid spectrum of diseases. These eyes are characterised by a thickened choroid, attenuation of the choriocapillaris and dilated Haller’s layer vessels , 47. SevA thicker choroid was shown to be associated with a poorer anatomical response to initial loading doses of anti-VEGF . Recent Pigment epithelial detachments (PEDs) are a hallmark feature of PCV , 56. PEDCurrently, neither choroidal thickness nor PED have been consistently shown to be associated with outcomes in patients treated for PCV. Most studies have used subfoveal or central choroidal thickness and maximum height or width of PED, or merely the presence or absence of PED. These point measurements and binary grading criteria may not fully encompass the effects of these features on the disease process or activity. With recent advances in segmentation algorithms, volumetric analysis of retinal pathological features such as IRF and SRF have been suggested as useful biomarkers for predicting treatment response , 57, 58.One of the core goals of treatment for neovascular maculopathies is to minimise treatment burden for the patient. There has been considerable effort in the field to either modify the delivery of currently available drugs through less intensive regimens or develop new drugs with the aim of improving treatment durability, efficacy, or safety, compared to currently available agents. While most ongoing registration clinical trials are aimed at nAMD, it is likely that in these cohorts, a subset are PCV. Increasingly, there is interest in investigating the efficacy of these newer agents on PCV.Brolucizumab is a recently available antibody fragment developed for the management of nAMD and other exudative maculopathies and was found to be similarly efficacious but more durable than aflibercept in the phase 3 HAWK and HARRIER trials , 60. SubAnother upcoming antibody for nAMD treatment, faricimab, is a bi-specific monoclonal antibody that binds VEGF-A and angiopoietin-2 (Ang-2), the latter being up-regulated in neovascular membranes and promoting vascular leakage in combination with VEGF-A , 65. RecAn alternative to regular intravitreal injections for long-term nAMD treatment is the surgically implanted port delivery system (PDS) for ranibizumab . The PDSHeterogeneity among PCV lesion characteristics and treatment responses is well recognised. In EVEREST II better visual gains were achieved, somewhat predictably, among those with younger age, poorer baseline vision, and smaller PCV lesion size for patients in the ranibizumab monotherapy arm . Higher The end-stage phenotypes of nAMD are well described and can represent a stage of disease in which treatment is often futile. Both fibrosis and macular atrophy have been associated with various baseline clinical and treatment features such as nAMD subtype, visual acuity and frequency of treatment. , 71–75 TIn typical nAMD, reports of up to 10-year outcomes are available , 77. In Therapies that directly address choroidal congestion may be effective for PCV treatment due to the strong evidence for choroidal features playing a role in the pathophysiology of PCV. Currently, PDT offers the most potential as a therapeutic option that targets the choroid. Some studies have demonstrated a reduction in CVH and choroidal thickness after PDT –85. FurtMost current PCV treatment strategies still hinge on the role of VEGF as a mediator of choroidal neovascularization and vascular permeability, a role which has been appreciated for 25 years . More reThis review demonstrates how the understanding of PCV has evolved with imaging studies and therapeutic trials. These advances have in turn translated into treatments, which promote sustained functional outcome and are aligned with the pathophysiology of the condition. There remains significant heterogeneity among retinal physicians in terms of preferred PCV treatment approaches, although clinical outcomes have improved substantially since the initial discovery of PCV. Recurrence of the disease 2–3 years after successful treatment is still a major concern. Future work which addresses the unique aspects of this condition will no doubt provide additional treatment options specifically tailored for PCV in the form of expanded drug choice and alternative dosing regimens, likely with a strong focus on improved treatment durability and reduced treatment burden.


The human microbiome has attracted attention for its potential utility in precision medicine. Increasingly, more researchers are recognizing changes in intestinal microbiome can upset the balance between pro- and anti-inflammatory factors of host immune system, potentially contributing to arthritis immunopathogenesis. Patients who develop rheumatoid arthritis from undifferentiated arthritis can face multiple irreversible joint lesions and even deformities. Strategies for identifying undifferentiated arthritis patients who have a tendency to develop rheumatoid arthritis and interventions to prevent rheumatoid arthritis development are urgently needed. Intestinal microbiome dysbiosis and shifts in the miRNA profile affect undifferentiated arthritis progression, and may play an important role in rheumatoid arthritis pathophysiologic process via stimulating inflammatory cytokines and disturbing host and microbial metabolic functions. However, a causal relationship between microbiome–miRNA interactions and rheumatoid arthritis development from undifferentiated arthritis has not been uncovered yet. Changes in the intestinal microbiome and miRNA profiles of undifferentiated arthritis patients with different disease outcomes should be studied together to uncover the role of the intestinal microbiome in rheumatoid arthritis development and to identify potential prognostic indicators of rheumatoid arthritis in undifferentiated arthritis patients. Herein, we discuss the possibility of microbiome–miRNA interactions contributing to rheumatoid arthritis development and describe the gaps in knowledge regarding their influence on undifferentiated arthritis prognosis that should be addressed by future studies. Rheumatoid Arthritis (RA) is an autoimmune disorder that affects more than just the joints particularly fingers and toes, and causes significant morbidity . RA is fImmune dysbiosis profiles, regardless of findings from early serological examination, recent clinical imaging, synovial fluid examination, or synovium biopsy, have been reported to successfully identify patients presenting with UA who were likely to have their disease progress to RA , 6, 7. WThe human intestinal microbiome has attracted attention for its potential utility in precision medicine. Microbiome–host immune system interactions occur via microbial antigens and metabolites ; changesMountains of studies also showed that alterations in miRNA expression contribute to susceptibility of RA/UA  displayed more Th17 cells in their large intestine compared with mice colonized with healthy control fecal samples. Furthermore, severe Th17 cell-dependent arthritis appeared in the RA-SKG mice after their injection with low doses of the fungal component zymosan, whereas there were no signs of arthritis when GF-SKG mice were injected with zymosan. These results indicate that intestinal microbiota dysbiosis dominated by P. copri can lead to arthritis. Intestinal P. copri may contribute to the development of arthritis via the action of superoxide reductase and adenosine phosphate phosphoryl sulfate reductase, the genes for which have been detected in its genome [A high elopment . Maeda eelopment  colonizes genome . These ts genome .Collinsella, the abundance of which was positively correlated with α-aminoadipic acid and asparagine serum levels and related to IL-17A production [Collinsella can change the intestinal permeability and disease severity of mice with experimental arthritis. Together, these findings confirm that certain intestinal bacteria can drive a pathologic immune response toward RA in the host and increase an individual’s risk of developing RA.Another study found that some of the low-abundance microbes in the healthy subject controls group were very abundant in untreated RA patients, such as oduction . Based o+ regulatory T (Treg) cells via the vitamin D receptor, and knocking out the bile acid metabolic pathways of intestinal symbiotic bacteria  inhibited their ability to induce RORγt+ Treg cells in murine colons [Although a causal relationship between the intestinal microbiome and RA development has not yet been comprehensively depicted, it is now clear that the microbiome–metabolite–immune system axis is involved in RA immunopathogenesis. Intestinal microbes maintain homeostasis with the host immune system via their constituents and metabolites. The regulatory effect of metabolites on host immune cells is a vital component of intestinal microbiome–host immune cell interactions; these can trigger chronic inflammation and autoimmunity, which are involved in RA initiation. For example, the short-chain fatty acids and aromatic amines can regulate immune cells through free fatty acid receptor (FFAR) 2, FFAR3, or G protein-coupled receptors metabolites, and they participate in many host immune pathophysiologic processes . Additioe colons . Additioe colons , and thee colons . HoweverAn imbalance in human intestinal microecology, along with the associated changes to the intestinal microbiota metabolic profile, such as a decrease of specific metabolites and the loss of metabolite diversity, will negatively affect the host immune response. Studies on patients with osteoarthritis found that gut microbiome dysbiosis is involved in bacterial metabolite dysbiosis and joint degeneration , and simHaemophilus sp. was enriched in the oral and intestinal flora of healthy controls, and its abundance in the patient group was inversely proportional to the titer of RA autoimmune antibody; Lactobacillus salivarius was enriched in the plaque, saliva, and stool of RA patients, especially those with a highly active condition; and, compared with healthy controls, the abundances of some functional genes in the oral and intestinal microorganisms of RA patients were significantly different . These findings suggest that abnormalities in the abundance of these functional genes play an important role in the main pathophysiologic processes of RA. In summary, the intestinal microbiome, as well as products of its co-metabolism with the host, can induce host autoimmune diseases and affect RA development.Although many factors contribute to RA development, the intestinal microbiome has recently been identified as an important pathogenic factor in RA initiation and progression. The contribution of microbiome dysbiosis to RA immunopathogenesis was first reported comprehensively by Zhang et al. , who comAbnormal miRNA profiles play a pivotal role in the pathogenesis of many joint injury diseases . Using RBecause of the stability, non-invasiveness, and sensitivity of miRNAs, the abnormal expression of miRNAs might be useful for disease diagnosis –65. The Studies on the role of microbiome dysbiosis in RA development have almost invariably focused on exploring the interaction network between the microbiome, its metabolites, and host immune and miRNA profiles. However, an etiopathogenic role of specific bacteria cannot be inferred by association alone. Therefore, integrating multi-omics studies on RA immunopathogenesis will be important for elucidating targetable mechanisms in cases of preclinical and established RA.The intestinal microbiome composition varies widely among different people; however, for an individual, the composition of the intestinal microbiome is relatively stable, and the structure of its core communities will not change with temporary changes to diet and lifestyle , 69. HumFusobacterium nucleatum and Escherichia coli) to regulate the transcription and expression of bacterial genes, thus affecting intestinal bacteria growth and shaping the composition of intestinal flora. When these researchers specifically knocked out Dicer, an enzyme responsible for miRNA processing, in murine small intestinal epithelial cells and Hopx-positive cells, fecal miRNA was reduced, and the mice showed symptoms of uncontrolled intestinal bacteria growth and colitis aggravation. Transplantation of the intestinal miRNA from normal mice to these defective mice was able to restore the intestinal microecological balance and improve the physical condition of the animals. Additionally, miRNAs’ regulation of microbial gene expression and growth was also reported in neurodegenerative diseases [Notably, miRNA can also shape the intestinal microbiota composition and regulate the activity of intestinal bacterial genes . Becausediseases .Host miRNA action provides an important mechanism for maintaining intestinal microbial homeostasis. In addition to the intestinal flora being related to the host extraintestinal immune function, it is also capable of affecting the host extraintestinal miRNA expression, known as the “microbiome–miRNA axis” Fig. . Its rolStudies on the mechanisms of development for host extraintestinal diseases have found that the intestinal microbiome is related to the host miRNA regulatory network. Abnormal miRNA profile changes are related to a variety of diseases, and their role in arthritis development is clear. Manipulating the intestinal microbiota and miRNA may improve treatment for this disease.Administering DMARDs to patients during the early initiation of arthritic disease is beneficial for relieving disease activity and radiographic joint damage . Thus, iIn the preclinical stages of RA, even before synovial biopsy and joint MRI show joint tissue damage, antibody to cyclic citrullinated peptide (anti‐CCP) and rheumatoid factor (RF) are already detectable in the peripheral blood . FurtherMulticenter studies with larger cohorts that investigate shifts in the clinical variables of patients with different UA prognoses will be vital to predicting the future development of RA in UA cohorts. Some clinical variables, such as anti‐CCP levels, polyarthritis, symmetric arthritis, and erosions visible on radiographs, have the potential to predict future RA development in UA cohorts. For example, the Leiden prediction rule, which takes into account the tender joint count, duration of morning stiffness, and duration of arthritis, was reported to have a potential role in predicting RA development . HoweverMany investigations on RA patients have revealed microbiome dysbiosis and abnormal miRNA profiles in these individuals. Emerging evidence suggests a bidirectional regulatory mechanism between the intestinal microbiota and miRNA in patients with UA/RA during the presentation of UA disease, and the intestinal microbiome may affect an individual’s UA prognosis. Additionally, the microbiome and miRNA have the highest specificities and positive predictive values for human health and disease states .The role of the microbiome and miRNA in the process of UA evolving into RA is an active area of RA research, and the mechanism of interaction is still unclear. Increased understanding of how these two factors interact and of their involvement in disease progression may provide mechanistic insight into RA development and lead to improved treatments for modifying UA and preventing RA. Additionally, we speculate that the miRNA profile as well as the microbiome composition and function differ between the subgroup of UA patients who progress to having RA and those who present directly with RA. Although key alterations in the oral and intestinal microbiomes have been demonstrated in patients who present with RA, the natural microbiome characteristics in patients who present with UA and subsequently develop RA are unknown, as are the shifts that occur during this progression. Therefore, we recommend that additional research be conducted on the abnormal alterations (dysbiosis) in the intestinal microbiome and miRNA of individuals as their UA evolves into RA.


The Sentinel System is a major component of the United States Food and Drug Administration’s (FDA) approach to active medical product safety surveillance. While Sentinel has historically relied on large quantities of health insurance claims data, leveraging longitudinal electronic health records (EHRs) that contain more detailed clinical information, as structured and unstructured features, may address some of the current gaps in capabilities. We identify key challenges when using EHR data to investigate medical product safety in a scalable and accelerated way, outline potential solutions, and describe the Sentinel Innovation Center’s initiatives to put solutions into practice by expanding and strengthening the existing system with a query-ready, large-scale data infrastructure of linked EHR and claims data. We describe our initiatives in four strategic priority areas: (1) data infrastructure, (2) feature engineering, (3) causal inference, and (4) detection analytics, with the goal of incorporating emerging data science innovations to maximize the utility of EHR data for medical product safety surveillance. It is an important resource that informs drug labeling, drug safety communications, FDA Advisory Committee meetings, and other regulatory decisions4. Health insurance claims data currently form the backbone of Sentinel, owing to their complete capture of outpatient pharmacy dispensing records, medical encounters, and hospitalizations during well-defined periods of health plan enrollment. Reliable implementation of drug safety analyses is achieved in a timely manner within Sentinel through the Active Risk Identification and Analysis (ARIA) system, which consists of modular programs that apply sophisticated epidemiologic study designs and analyses to distributed health insurance claims data organized in a common data model1.The United States Food and Drug Administration (FDA)’s Sentinel System (referred to as “Sentinel” hereafter) uses distributed analytic tools and curated real-world longitudinal health insurance claims data for more than 100 million people from participating healthcare systems to generate insights regarding the safety of medical products5. Linking electronic health records (EHRs), which contain granular information related to clinical parameters, with insurance claims will likely address some of the current gaps in Sentinel’s capabilities. In 2019, Congress required the FDA to create a Medical Data Enterprise to enhance the Sentinel infrastructure by incorporating EHR data from at least 10 million lives6.In a recent analysis of ARIA capabilities, some of the most frequently cited reasons for the inability of using the current claims-based Sentinel for safety investigations included the lack of clinical details to accurately identify health outcomes, missing or inaccurate measures of important confounding variables, or unavailability of computable phenotyping algorithms to identify study populations with acceptable accuracy7. In this report, we describe a roadmap of the newly launched FDA Sentinel Innovation Center to strengthen the Sentinel System by outlining key challenges and proposed initiatives to address them.With all the opportunities for improvement, the inclusion of additional EHR data also introduces several methodological challenges that need to be addressed to facilitate robust analyses using a large-scale data infrastructure of combined EHR and claims data. The FDA has outlined an approach for achieving these goals in a 5-year Sentinel System strategic planTo expand Sentinel’s access to EHR data, a first-order goal is to develop the organizational framework and establish the governance, harmonization, and quality assurance processes for ensuring high-fidelity, fit-for-purpose data to support queries of regulatory importance. To support causal conclusions, establishing a clear temporal sequence of events based on data from sources with near-complete longitudinal capture is imperative. As most EHR sources in the US lack the ability to capture data when individuals receive care outside of the contributing healthcare systems, linkage of EHRs to insurance claims, which captures longitudinal data regardless of the care settings, is necessary to understand the completeness of longitudinal data. In establishing a query-ready distributed data network containing EHRs, the Sentinel Innovation Center will address key regulatory needs including determining where to source the EHR data with standing linkage to insurance claims and defining the minimum data elements necessary in order to address use cases that are currently difficult to address. Additionally, we will outline principles and strategies for determining how to organize both the structured, semi-structured and unstructured EHR data alongside insurance claims data in a common data model to facilitate standardized query implementation Fig. .Fig. 1Co8. As regulatory decisions are predicated on inferring causal relations between a medical product exposure and adverse outcomes, a causal analysis framework fitting nonrandomized treatment allocation and secondary data is needed9. Even for signal identification based on data mining methods, attention to principles including clearly established temporality of confounder assessment preceding exposure followed by outcome surveillance, paired with analytic strategies that reduce confounding, is required to limit the number of spurious signals12. For signal refinement and evaluation, in addition to these important principles, further considerations include explicitly specifying comparison groups, study populations, and specific outcome definitions ideally contemplated in a hypothetical ‘target’ trial which investigators then emulate in the secondary data of Sentinel14. Analyses further should be accompanied by robustness evaluations to address the consistency of evidence with respect to alternative investigator decisions in study design, analysis, or variable measurement. To clarify challenges in developing and applying causal methods that leverage both claims and EHR data sources, the Sentinel Innovation Center will develop a causal analysis framework proposing a stepwise process that systematically considers key choices with respect to design and analysis that influence the validity of studies conducted with nonrandomized data. A standardized “industrial” process that will be outlined in this framework will serve as a valuable tool to inform the conduct and assessment of the quality of nonrandomized studies of drug-outcome evaluation.To comprehensively monitor the safety of marketed medical products, Sentinel investigations focus on both signal identification, which is intended to generate hypotheses regarding unsuspected adverse events, as well as signal refinement and evaluation, which is intended to test previously generated hypotheses and identify susceptible populations15 and (2) to identify and expeditiously validate health outcomes of interest in the postexposure space (right side) by augmenting claims-based algorithms with EHR-based data that may be structured, semi-structured, or unstructured. The Innovation Center has formed four main domains as strategic priority initiatives to deliver a query-ready, large-scale data infrastructure of combined EHR and claims data: data infrastructure, feature engineering, causal inference, detection analytics  codes for diagnoses and National Drug Codes (NDC) for filled prescriptions. Some of the EHR-based data such as administrative data, medication orders, and most laboratory testing results are recorded as structured or semi-structured fields, but a vast amount of potentially useful information is stored in visit notes , radiology reports or images, and discharge summaries as unstructured data. Substantial engineering is needed to identify features from unstructured data that can be extracted and organized as structured data.19 and focus on developing a general framework for efficient and standardized processes. Another set of activities aim to build a semi-automated system of confounding adjustment that uses generalized NLP tools to enable large-scale extraction of features that appear sequentially and may serve as indicators of patients’ health trajectory. Finally, initiatives are also underway to improve the generalizability and transportability of NLP approaches across sites using statistical learning approaches20.Natural language processing (NLP) and automated feature extraction are essential mechanisms to support scalable computable phenotyping from EHRs in signal detection and signal refinement activities. Development of automated feature extraction workflows that allow for time-contextualization is critical to enable the determination of temporality in confounder, exposure, and outcome assessment in Sentinel queries. However, there are numerous challenges in using these approaches at scale in national consortia. NLP tool performance between sites has been a challenge due to systematic data changes. Tool development further needs to be tailored to the eventual application of the derived features. For instance, identification of health outcomes of interest needs focused tools to ensure optimal performance characteristics including positive predicted value and specificity, while identification of potential confounders may utilize more flexible tools utilizing unsupervised approaches for high-dimensional feature vector generation. To address these challenges, the Sentinel Innovation Center has initiated a range of activities. The first set of projects aims to develop and validate algorithms for the identification of health outcomes of interest using focused NLP tools combined with machine learning approaches to identify complex concepts such as suicidal ideation. This work will expand on prior Sentinel activities that have demonstrated the proof of concept for use of algorithmic approaches in improving outcome identification21 to accommodate relatively smaller underlying populations. Tradeoffs when deviating from traditional design choices to accommodate available data assets need to be thoroughly investigated. Other unique challenges when using EHR for the outcome and confounder measurement include nonrandom missingness, or similarly the selective presence of data such as medical tests that may be ordered in light of the patients’ prognosis, or incompleteness that occurs when outcomes recorded outside of the care systems are not available (“data leakage”). The Sentinel Innovation Center will focus on characterizing these challenges and developing strategies, methods, and tools to address them.Typical Sentinel investigations for drug safety conducted using insurance claims data sources have relied on restrictive study designs such as the active comparison of new user designs to achieve internal validity given the availability of large underlying populations; however, the use of EHR-claims linked sources may require alternate design choices, such as prevalent new user design23. Super Learner, which is an ensemble algorithm for predictive modeling, can data-adaptively model confounder summary scores, such as the propensity score, and the outcome to address model misspecification in the setting of complex and high-dimensional data settings of EHRs. TMLE can incorporate data-driven methods for high-dimensional confounder selection to empirically identify confounder information not specified by investigators. Developing scalable tools to implement these innovative methods in real-time will enhance the ability of Sentinel to address the common threat of confounding. Additionally, the Innovation Center will also investigate methods such as negative control outcomes or exposures and enhance existing tools for quantitative bias analyses24 to better understand the robustness of findings, including the impact of residual confounding.Residual confounding due to selection into treatment groups driven by outcome risk factors is another salient challenge in nonrandomized studies. The issue is accentuated when using data that lack clinical granularity such as insurance claims. Availability of EHR sources that contain richer clinical information on factors not readily available in claims hold promise to improve confounding adjustment in nonrandomized studies. The Sentinel Innovation Center will evaluate the feasibility of improved confounding adjustment from EHR-based variables through a combination of automated feature generation algorithms and advanced statistical and machine learning approaches such as Super Learner and Targeted Maximum Likelihood Estimation (TMLE)25. Incorporating NLP-assisted technology that can sift through patient charts and present the most relevant chart based on pre-specified key terms to human expert reviewers can add further efficiency to the process. The Sentinel Innovation Center will consider methodologic research to improve outcome identification and validation, which is a vital requirement for reliable evaluation of medication safety in Sentinel.Availability of additional clinical information in EHR further opens new opportunities to (1) identify outcomes that are generally not identifiable with claims data alone or (2) to efficiently validate claims-based algorithms in a subset of patients with EHR data available. The use of advanced methods based on machine learning and NLP to expedite outcome identification or validation have the potential to increase the efficiency of traditional drug safety evaluations. For instance, data-adaptive validation techniques where human experts review batches of patient charts for endpoint validation based on claims or EHR data could be iteratively used to train algorithms to inform the selection of cases that have a higher likelihood of being a true positive in the next batch10. EHRs offer a potentially promising complementary source of information for medication safety signal detection but may require tailored approaches to account for and leverage differences in data content and structure compared to insurance claims. Specifically, unstructured clinical narratives recorded in EHR may provide more complete capture of subtle adverse events that may not trigger formal coding or medical interventions, aspects that are observable in claims data. The addition of detailed information presents an opportunity to expand signal detection efforts that are currently used in Sentinel. While NLP-based identification of adverse events from unstructured clinical notes is feasible with currently available methods, relational identification of newly occurring adverse events in a temporal sequence to specific medication exposures is complex and the subject of active research26. The Sentinel Innovation Center plans to develop a methodological framework and conduct empirical evaluations to identify and test the most promising approaches for EHR-based signal detection.Data mining approaches such as TreeScan have been developed in insurance claims data for signal detection in the Sentinel infrastructure based on the grouping of ICD diagnosis codes into hierarchical levels14.The Sentinel Innovation Center will launch several demonstration projects focusing on use cases typical for Sentinel; associations of medications for chronic conditions with infrequently observed outcomes where EHR data linkage has the potential to offer enhancements with respect to population identification, confounding adjustment, or outcome measurement. In these demonstration projects, we will emulate the corresponding target trial using principles and methodology developed across several Sentinel Innovation Center initiatives described above. When available, we will benchmark results against those observed in the corresponding pivotal clinical trial findings27, to prepare and be able to register study protocols for future Sentinel queries. Additionally, adherence to principles for transparent reporting of analytic assumptions and diagnostics in line with good reporting practices28 as well as transparent research practices including sharing of the analytic codes will be emphasized.Transparent communication of study specifications in a pre-registered protocol, akin to a prospective trial protocol, is a feature that helps increase confidence in results of hypothesis-confirming studies from nonrandomized studies using secondary EHR-claims data. A focus of the Sentinel Innovation Center will be to facilitate EHR adaptation of existing tools such as the structured template and reporting tool for real-world evidence (STaRT-RWE) planning, implementation and communication templateEnhancements in the current Sentinel system proposed by the Sentinel Innovation Center that are summarized in this report will be achieved through strategic investment in focused research projects working in harmony. The new system containing granular clinical information through the integration of EHRs will broaden the scope of the current system by expanding on the types of medication safety and effectiveness questions that are insufficiently addressed by insurance claims only. This may include questions where insurance claims data do not have sufficient information to identify the underlying population of interest, the outcome of interest, or a critical confounder to support a valid comparative analysis. Additionally, this system will also strengthen investigations that are possible to implement with insurance claims only through activities such as enabling extensive clinical characterization in a subset of patients selected for treatment with different medications and facilitating outcome algorithm development and validation for implementation in broader insurance claims-based network.29 to deliver a query-ready distributed data network containing EHR linked to claims and reusable analysis tools to enhance the capabilities of the current system. These initiatives will incorporate data science innovations, such as scalable natural language processing and machine learning, to maximize the potential of EHR for medical product safety surveillance.The FDA Sentinel Innovation Center has outlined a set of initiatives and a project portfolio


To explore general practitioners’ (GPs’) perceived indicators of vulnerability among pregnant women in primary care.A qualitative study with semi-structured in-depth focus group interviews.General practices located in a mixture of urban, semi-urban and rural practices throughout the Region of Southern DenmarkTwenty GPs.Through qualitative analysis with systematic text condensation of the interview data, the following themes emerged: (1) obvious indicators of vulnerability—i.e. somatic or psychological illnesses, or complex social problems and 2) intangible indicators of vulnerability – i.e. identification depended on the GPs’ gut-feeling.From the GPs’ perspective, the concept of vulnerability in pregnancy were perceived as the net result of risk factors and available individual and social resources, with a psychosocial etiology as the dominant framework.The GPs demonstrated a broad variety of perceived indicators of vulnerability in pregnancy; most importantly, the GPs were aware of a group of pregnant women with intangible vulnerability mainly representing low resilience. Despite not fitting into the GPs' perceived concept of vulnerability, the GPs had a strong gut feeling that these women might be vulnerable. Misjudging the resources of pregnant women due to their physical appearance could delay the GPs’ identification of vulnerability. Future studies should explore the challenges GPs experiences when assessing vulnerability among pregnant women.The online version contains supplementary material available at 10.1186/s12875-021-01439-3. Vulnerability among fertile women is increasing due to low psychosocial resources, such as social problems and mental health problems . UndetecVulnerability in pregnancy is described in the literature as psychosocial problems (i.e. history of anxiety or depression before or during pregnancy) or social problems  between gestational week 6–10, with the purpose of evaluating the need for extra support during pregnancy by assessing the pregnant women's comorbid risks and psychosocial resources . HoweverAs GPs, our pre-assumptions were formed through years of experience working with pregnant women and families in urban and rural settings and collaborating with social-obstetric outpatient units. We have experienced how vulnerable pregnant women were sometimes overlooked in pregnancy consultations and went through pregnancy without support, and some developed perinatal depression. Or pre-assumption was that different perceptions of indicators of vulnerability in pregnancy affected the GPs’ behavior when approaching the risk and resources of a pregnant women. The aim of this study is to explore GPs’ perceptions of what indicates vulnerability in pregnancy.This is a cross-sectional qualitative study based on semi-structured in-depth focus group discussions with GPs. It is part of a multi-method project exploring barriers and facilitators in assessing and in managing the antenatal care of vulnerable pregnant women from a user-perspective of the GPs. We chose the qualitative methodology to explore GPs perceived indicators of vulnerability in pregnancy. A qualitative design enabled us to explore the GPs understandings of and perceptions of indicators of vulnerability in pregnancy in the terms of “what, why and how”. The safe environment during interview encouraged them to disclose situations of deficient performances when identifying vulnerable pregnant women, and the dialogue rendered the GPs to reflect on their own practices.the biopsychosocial model by Engel  might not have a proper network to support them, though we also have cases of vulnerable women where parents are available to support them, which may be their saving”. “A history taking indicating poor network with loneliness or missing support from spouse evoked the GPs gut-feeling of intangible vulnerability. Contrary, a history indicating an available network of social support were perceived to increase these women’s chance of having a healthy pregnancy and motherhood. As a female GP stated:A retrospective realization of missed vulnerability: Interestingly, the GPs described being guided by the woman’s appearance in their evaluation of the patient’s resources and risks of vulnerability. If a woman appeared with normal interpersonal behavior and well dressed, they were less likely to elaborate on skills of resilience, and these women could go undetected until developing obvious signs of depression. As a female GP said.I had a pregnant woman where everything in her patient file looked fine, but when she came for the five weeks examination of her child I discovered that there was no eye contact with the baby, and subsequently I realized that the mother had a severe postpartum depression – and I thought ‘why didn’t I discover that?’” “I have mothers who are well educated and with strong resources but cannot cope with the task of parenthood. They are so focused on themselves and training and everything must be perfect. They contact me all the time about minor things as they cannot judge the needs of their own child(..) I think that represents a vulnerability(..) So next time she gets pregnant I would definitely categorize her as vulnerable” “Debates among GPs during interviews led some GPs to realize how they often recognized this intangible vulnerability retrospectively. Some GPs told how their gut feelings of intangible vulnerability were evoked years later, when the women or couples presented with frequent child consultations for minor things, such as simple colds, due to their insecurity in judging the child’s needs.“They can easily trick you. I remember a woman, very nicely dressed, coming for her first antenatal consultations. She was a new patient and I had no previous medical record on her. We went through her pregnancy record nice and easy, I asked about alcohol use and she said there was none. At the end of the visit she asked how should go about getting her alcohol treatment transferred to the local alcohol rehab center. She was not currently using alcohol, and therefore had answered no to all the questions. It’s hard when we don’t know them. Based on her appearance I had no idea that she was in alcohol rehab” Especially challenging situations was when pregnant women was new affiliated in the clinic and no doctor-patient relation existed. A GP told how she was misguided by a woman’s physical appearance.The GPs perceived vulnerability in pregnancy as the net result of psychosocial stressors and available individual resources and social supportive network. They classified vulnerability according to its obviousness. Obvious indicators of vulnerability were known complex social problems, mental health problems including history of abuse and severe somatic comorbidity. Some pregnant women were perceived with intangible indicators, evoking the GPs’ gut feeling of vulnerability- where low resilience was prominent. Pregnant women with seemingly normal socioeconomic resources could delay the identification of vulnerability. This was especially the challenge when there was no pre-existing doctor-patient relation.Strengths of this study were the semi-structured qualitative approach using focus group interviews and using COREQ criteria to ensure transparency . The choThe research group possessed experience from years of working with antenatal care in general practice and from collaborating with doctors and midwifes in the social-obstetric outpatient clinic. This empirical clinical perspective was a strength as it gave a comprehensive insight into the working environment and possible challenges GPs face when defining the concept of vulnerability in pregnancy. Though, we acknowledge that our experience and preconceptions might have affected the generation and interpretation of the qualitative data, and that addition of other professional expertise might have found other perspectives of what indicates vulnerability in pregnancy.The use of convenience sampling due to slow recruitment, could be a weakness of this study. Only GPs from partnership practices participated, and these might have been GPs with a natural interest in the topic, which could limit the transferability of the findings. Though it was not an inclusion criterion, the recruited GPs varied broadly in their experience with conducting pregnancy consultations, and represented many different perceptions of indicators of vulnerability in pregnancy. This indicates that we recruited GPs with varying interest in the field of antenatal care. Moreover, it is a strength that we achieved diversity regarding seniority, gender, and practice location from urban, semi-urban and rural areas representing patients from different socioeconomic layers. The GPs in the study represented many different perceptions of indicators of vulnerability in pregnancy, and therefore, we believe that our findings could represent the perceptions of GPs from other Danish regions.This study adds knowledge to a sparsely covered area, about GPs’ perceived indicators of vulnerability in pregnancy. Previous studies focused on GPs’ perceptions of perinatal mental health problems, where vulnerability was classified as a risk factor of perinatal mental health problems. However, GPs’ understandings of indicators of vulnerability were not explored , 33, 34.Studies have shown that GPs are more aware of postpartum depression, and that perinatal depression is underdiagnosed by GPs, with up to 50% missed cases , 26, 33.the biopsychosocial model by Engel and the concept of organismic thinking by McWhinney. Both concepts from Engel and McWhinney stresses how illness develops through complex interactions of biological, psychological, and social factors. Coexisting social or psychological factors may trigger development of illness, such as depression, with or without biological genetic predispositions of depression. In this way the biopsychosocial model may explain the obvious and intangible indictors of vulnerability in pregnancy as a precursor for complications in pregnancy, birth, and childhood.This study’s findings on GPs’ perceptions of obvious indicators of vulnerability in pregnancy is supported by The findings that GPs distinguishes vulnerability according to their apparent severity is in line with other findings from nursing literature, where severe vulnerability is defined as the combination of compromised capacity for self-protection while being dependent on health support to prevent development or deterioration of illness .the capacity of the family as a functional system, to withstand and rebound from stressful life challenges”. These capacities involves many key processes—such as making meaning of adversity, having a positive outlook, cooperative parenting, help seeking behavior and communication solving. Similar, the intangible indicators of vulnerability in pregnancy, such as coping problems and relationship challenges in pregnancy and reluctancy to seek help can express low resilience.The GPs’ perceptions of intangible indicators of vulnerability covering traits of low resilience, is supported by theories of Family resilience by Walsh . Walsh dThe finding of GPs’ having gut feelings indicating an intangible vulnerability in a pregnant woman is in line with findings from other studies, which described gut feelings among GPs as a sense of alarm that somethings is wrong, even if no objective argument was present –39. In tThis study has demonstrated how GPs perceive indicators of vulnerability in pregnant women according to their apparent severity and obviousness. Obvious indicators of vulnerability in pregnancy were previously known social determinants of health, psychiatric diseases, or chronic somatic diseases, where a psychosocial etiology was the most dominant framework. The GPs described intangible indicators of vulnerability such as odd contact raising suspicion of undetected psychiatric disease, and signs of low resilience in the women or her environment. However, intangible indicators were also recognized retrospectively in women appearing with normal resources, especially when the GP had no relation to the patient. If the GPs were more aware on their gut feelings of intangible indicators for vulnerability, it would elicit the need for a sound history taking of the pregnant woman’s social network and skills of resilience. As a consequence, this might increase the GPs’ awareness on the pregnant woman’s risk of developing perinatal depression.Further evidence is needed on the challenges GPs experience when assessing and addressing indicators of vulnerability in pregnant women, and when managing their care through engagement in cross-sectoral collaboration. Changes might be needed in the organization and structure of antenatal care in general practice and in the cross-sectoral antenatal care collaboration to ensure that proper attention is paid to women with intangible vulnerability.Additional file 1Additional file 2