Journal of Clinical Epidemiology最新文献

{"title":"A simulation study showed that linear regression and Mann-Whitney test can be used to analyze the days alive and at home by day 30 outcome in a randomized controlled trial","authors":"Jonathan Alistair Cook","doi":"10.1016/j.jclinepi.2025.111674","DOIUrl":"10.1016/j.jclinepi.2025.111674","url":null,"abstract":"<div><h3>Background and Objectives</h3><div>The aims of the work were to consider the properties of the days alive and at home by day 30 (DAH30) from a statistical perspective, and to conduct a simulation study exploring the use of simple (unadjusted) linear regression and Mann-Whitney test as the method of analysis reflect realized analysis options.</div></div><div><h3>Study Design and Setting</h3><div>The days alive and at home by day 30 (DAH30) has been proposed a patient-centric outcome, and clinically relevant outcome suitable for clinical trials. It has unusual statistical properties, and suitability of standard statistical analysis methods is unclear. The properties of DAH30 were reviewed. Simulations based upon 1:1 allocation in an randomized controlled trial (RCT) based upon empirical data were conducted reflecting different additive and realized (reflecting the DAH30) treatment effects, sample sizes and distributions with varying and central locations and zero value level. A variety of metrics were used to assess performance (including bias, coverage, and rejection rate).</div></div><div><h3>Results</h3><div>Linear regression provided a valid estimate of the unadjusted average treatment effect with an additive treatment. This was confirmed in terms of bias, estimation of variance, rejection rate in the absence of an effect, and coverage of the 95% confidence interval for the true realized effect. Mann-Whitney provided greater (power) than linear regression in some situations.</div></div><div><h3>Conclusion</h3><div>Simple linear regression is a reasonable analytic option for the DAH30 for estimating the average treatment effect in the RCT cohort (ie, an intention to treat, or “treatment policy” estimand) where zero-inflation is relatively low. Mann-Whitney test in some circumstances (small effects and smaller samples sizes) provides better ability (like for like) to detect a difference between the groups.</div></div><div><h3>Plain Language Summary</h3><div>Simple linear regression can be used to analyze DAH30 outcome in a randomized trial for a range of scenarios which were considered in this study (including relatively proportions of zero values). The DAH30's properties affect the treatment effect than can be estimated. Mann-Whitney test offered better ability to detect a difference of a smaller magnitude for smaller samples sizes.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111674"},"PeriodicalIF":7.3,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-impact trials with genetic and -omics information focus on cancer mutations, are industry-funded, and less transparent","authors":"Luigi Russo ,&nbsp;Leonardo M. Siena ,&nbsp;Sara Farina ,&nbsp;Roberta Pastorino ,&nbsp;Stefania Boccia ,&nbsp;John P.A. Ioannidis","doi":"10.1016/j.jclinepi.2025.111676","DOIUrl":"10.1016/j.jclinepi.2025.111676","url":null,"abstract":"<div><h3>Objectives</h3><div>To assess how genetics and -omics information is used in the most cited recent clinical trials and to evaluate industry involvement and transparency patterns.</div></div><div><h3>Study Design and Setting</h3><div>This is a meta-research evaluation using a previously constructed database of the 600 most cited clinical trials published from 2019 to 2022. Trials that utilized genetic or -omics characterization of participants in the trial design, analysis, and results were considered eligible.</div></div><div><h3>Results</h3><div>132 (22%) trials used genetic or -omics information, predominantly for detection of cancer mutations (<em>n</em> = 101). Utilization included eligibility criteria (<em>n</em> = 59), subgroup analysis (<em>n</em> = 82), and stratification factor in randomization (<em>n</em> = 14). Authors addressed the relevance in the conclusions in 82 studies (62%). 102 studies (77%) provided data availability statements and six had data already available. Most studies had industry funding (<em>n</em> = 111 [84.0%]). Oncology trials were more likely to be industry-funded (90.1% vs 64.5%, <em>P</em> = .001), to have industry-affiliated analysts (43.6% vs 22.6%, <em>P</em> = .036), and to favor industry-sponsored interventions (83.2% vs 58.1% <em>P</em> = .004). When compared to other trials, genetic and -omics trials were more likely to be funded by industry (84% vs 63.9%, <em>P</em> &lt; .001) and tended to be less likely to have full protocols (<em>P</em> = .018) and statistical plans (<em>P</em> = .04) available.</div></div><div><h3>Conclusion</h3><div>Our study highlights the current underutilization of genetic and -omics technologies beyond testing for cancer mutations. Industry involvement in these trials appears to be more substantial and transparency is more limited, raising concerns about potential bias.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111676"},"PeriodicalIF":7.3,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Funding matters: time to update preferred reporting items for systematic reviews and meta-analyses?","authors":"James Burgert,&nbsp;Georgia C. Richards","doi":"10.1016/j.jclinepi.2025.111678","DOIUrl":"10.1016/j.jclinepi.2025.111678","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111678"},"PeriodicalIF":7.3,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How should we assess trustworthiness of randomized controlled trials?","authors":"Jack Wilkinson, David Tovey","doi":"10.1016/j.jclinepi.2025.111670","DOIUrl":"10.1016/j.jclinepi.2025.111670","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111670"},"PeriodicalIF":7.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the use and usefulness of living guidelines for consumers: international online survey of patients' and carers' views","authors":"Anneliese Synnot ,&nbsp;Samantha Chakraborty ,&nbsp;Jessica Xue ,&nbsp;Hui Zhen Cheng ,&nbsp;Danielle Berkovic ,&nbsp;Tari Turner","doi":"10.1016/j.jclinepi.2025.111671","DOIUrl":"10.1016/j.jclinepi.2025.111671","url":null,"abstract":"<div><h3>Background and Objective</h3><div>Living guidelines contain continually updated, and potentially changing, clinical recommendations. The implications of living guidelines for consumers (eg, patients, carers, and people with lived experience) - particularly how living guidelines should be developed and disseminated – are yet to be established. The objective of this study was to explore consumers’ views about how best to support the use and usefulness of living guidelines to consumers.</div></div><div><h3>Methods</h3><div>This study used a qualitative (online survey) design. We invited consumers who were familiar with guidelines (living or conventional) to participate in the study. The survey was distributed globally. Recruitment was conducted via the Australian and international networks of the Australian Living Evidence Collaboration. We invited consumers who were familiar with guidelines (living or conventional) to participate in the study. The survey was distributed globally. Recruitment was conducted via the Australian and international networks of the Australian Living Evidence Collaboration. The 5–10 minute survey collected demographic data then, after introducing the living guidelines concept, asked questions about what living guidelines mean for consumers, how we might make them easy for consumers to find and use, and potential challenges to their use. We analyzed the data using inductive thematic analysis.</div></div><div><h3>Results</h3><div>Forty-five people (71% women) from 12 countries completed the survey. Participants were enthusiastic about the concept of living guidelines and what they might mean for consumers' ability to make informed health-care decisions and receive best care. They also identified potential challenges related to living guideline dissemination, such as low public awareness of guidelines and confusion about updated recommendations. Participants described practical strategies to support consumers’ awareness and use of, and access to, living guidelines. These included: meaningful involvement of consumers in the development and dissemination of living guidelines; raising awareness by promoting the guidelines widely through trusted health information sources and on social media; and using user-centered formatting and design principles (eg, considering accessibility needs, and publishing lay summaries with plain and culturally-appropriate language).</div></div><div><h3>Conclusion</h3><div>Consumers suggested a comprehensive range of dissemination strategies to support the use and usefulness of living guidelines to consumers, which largely reflect best practice in conventional guideline dissemination. Promoting and explaining the living nature of guideline recommendations might support their use by consumers. There should also be a close link between the living guidelines and any versions or additional content created for both consumers and clinicians.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111671"},"PeriodicalIF":7.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Larger sample sizes are needed when developing a clinical prediction model using machine learning in oncology: methodological systematic review","authors":"Biruk Tsegaye ,&nbsp;Kym I.E. Snell ,&nbsp;Lucinda Archer ,&nbsp;Shona Kirtley ,&nbsp;Richard D. Riley ,&nbsp;Matthew Sperrin ,&nbsp;Ben Van Calster ,&nbsp;Gary S. Collins ,&nbsp;Paula Dhiman","doi":"10.1016/j.jclinepi.2025.111675","DOIUrl":"10.1016/j.jclinepi.2025.111675","url":null,"abstract":"<div><h3>Background and Objectives</h3><div>Having a sufficient sample size is crucial when developing a clinical prediction model. We reviewed details of sample size in studies developing prediction models for binary outcomes using machine learning (ML) methods within oncology and compared the sample size used to develop the models with the minimum required sample size needed when developing a regression-based model (N_min).</div></div><div><h3>Methods</h3><div>We searched the Medline (via OVID) database for studies developing a prediction model using ML methods published in December 2022. We reviewed how sample size was justified. We calculated N_min, which is the N_min, and compared this with the sample size that was used to develop the models.</div></div><div><h3>Results</h3><div>Only one of 36 included studies justified their sample size. We were able to calculate N_min for 17 (47%) studies. 5/17 studies met N_min, allowing to precisely estimate the overall risk and minimize overfitting. There was a median deficit of 302 participants with the event (<em>n</em> = 17; range: −21,331 to 2298) when developing the ML models. An additional three out of the 17 studies met the required sample size to precisely estimate the overall risk only.</div></div><div><h3>Conclusion</h3><div>Studies developing a prediction model using ML in oncology seldom justified their sample size and sample sizes were often smaller than N_min. As ML models almost certainly require a larger sample size than regression models, the deficit is likely larger. We recommend that researchers consider and report their sample size and at least meet the minimum sample size required when developing a regression-based model.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111675"},"PeriodicalIF":7.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143015515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What happened next? A survey of review clients evaluating impacts of rapid reviews","authors":"Peter Bragge ,&nbsp;Emily C. Clark ,&nbsp;Veronica Delafosse ,&nbsp;Ngo Cong-Lem ,&nbsp;Diki Tsering ,&nbsp;Paul Kellner ,&nbsp;Alyssa Kostopoulos ,&nbsp;Maureen Dobbins","doi":"10.1016/j.jclinepi.2025.111673","DOIUrl":"10.1016/j.jclinepi.2025.111673","url":null,"abstract":"<div><h3>Objectives</h3><div>End-user evaluation of the impact of evidence syntheses is critical to demonstrating value. This study presents results of a survey evaluating the impact of rapid reviews undertaken by two teams based in Melbourne, Australia, and Hamilton, Canada.</div></div><div><h3>Methods</h3><div>Clients were invited to participate in a short written survey following delivery of a rapid review. Survey items encompassed reach, usefulness and format; interactions with the review teams; and overall satisfaction.</div></div><div><h3>Results</h3><div>Twenty-five completed surveys from 53 invitations were received pertaining to 19 rapid reviews conducted between September 2021 and October 2023. Topics encompassed COVID-19, health and behavior change; reports were an average of 31 pages; and were delivered over an average of 62 days. Evaluation findings were positive, with high satisfaction with reports and service delivery; very high satisfaction with report structure and length; good evidence of reach (reports read by decision makers and cited in other documents); and evidence that the rapid reviews made contributions to strategic planning, policy and program funding decisions.</div></div><div><h3>Conclusion</h3><div>Rapid reviews are making impactful contributions, alongside other inputs, to policy and practice. Further research is required to build this evaluation dataset; examine the balance between timeliness and methodological rigor in evidence synthesis; and explore models of delivery and capacity within and outside of government. It is also critical to promote implementation efforts to harness the full potential of rapid reviews and other evidence syntheses to impact the lives of citizens.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111673"},"PeriodicalIF":7.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accounting for differential exclusions in the Nordic-European initiative on colorectal cancer trial discloses stronger-than-reported effects of screening colonoscopy","authors":"Hermann Brenner ,&nbsp;Tim Holland-Letz ,&nbsp;Michael Hoffmeister ,&nbsp;Thomas Heisser","doi":"10.1016/j.jclinepi.2025.111669","DOIUrl":"10.1016/j.jclinepi.2025.111669","url":null,"abstract":"<div><h3>Objectives</h3><div>Recently, results on colorectal cancer (CRC) incidence and mortality reduction by the offer of screening colonoscopy were reported for the first time from a randomized controlled trial (RCT), the Nordic-European Initiative on Colorectal Cancer (NordICC) trial. Despite randomization, there was a substantially lower proportion of postrandomization exclusions of CRC cases due to cancer registry-recorded date of diagnosis before recruitment in the invited group than in the usual-care group. We aimed to evaluate the impact of such differential exclusions on the trial's effect estimates on CRC risk.</div></div><div><h3>Study Design and Setting</h3><div>We compared reported postrandomization exclusions of CRC cases due to cancer registry-recorded date of diagnosis, and we derived adjusted effect estimates on CRC risk accounting for the reported differential postrandomization exclusion of CRC cases in the invited group and the usual-care group.</div></div><div><h3>Results</h3><div>Reported postrandomization exclusion proportions of CRC cases were originally reported as 52/31,472 (0.17%) and 159/63,133 (0.25%) in the invited and usual-care group, respectively, (<em>P</em> &lt; .005) in an analysis, including participants from all four NordICCstudy countries and as 52/28,277 (0.20%) and 164/56,529 (0.29%) in the recent analysis of 10-year follow-up data from three of the countries (<em>P</em> = .018). Accounting for the differential exclusion proportions increased the estimated CRC risk reduction (95% CI) from originally reported 18% (7%–30%) to 25% (95% CI 13%–35%) in intention-to-screen analysis. Estimated reduction of CRC risk among screening attenders increased from originally reported 31% (17%–45%) to 50% (25%–69%) in adjusted per-protocol analysis.</div></div><div><h3>Conclusion</h3><div>Accounting for differential postrandomization exclusions of CRC cases leads to stronger-than-reported effect estimates in the so far only RCT on long-term effects of screening colonoscopy.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111669"},"PeriodicalIF":7.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the scientific integrity of the collected work of one author or author group","authors":"Jeremy Nielsen ,&nbsp;Esmée M. Bordewijk ,&nbsp;Lyle C. Gurrin ,&nbsp;Siddharth Shivantha ,&nbsp;Madeline Flanagan ,&nbsp;Sue Liu ,&nbsp;May M. Linn ,&nbsp;Kelly X. Zhou ,&nbsp;Rik van Eekelen ,&nbsp;Nicholas J.L. Brown ,&nbsp;Jim Thornton ,&nbsp;Ben W. Mol","doi":"10.1016/j.jclinepi.2024.111603","DOIUrl":"10.1016/j.jclinepi.2024.111603","url":null,"abstract":"<div><h3>Objectives</h3><div>No published methods for research integrity review include both statistical techniques applied to groups of randomized trials and individual assessment of papers. We propose a method based on practical experience of investigating data integrity across the collected papers of an author or author group.</div></div><div><h3>Study Design and Setting</h3><div>We report our approach to investigating the collected papers of an author or author group suspected of academic misconduct.</div></div><div><h3>Results</h3><div>In the investigation of the work of an author or author group, we recommend a systematic search for the work of the involved authors in PubMed, Google Scholar, and the Retraction Watch database, as well as a search of trial registries for unpublished clinical trials. Summary information from studies should be tabulated to assess consistency between study registration, execution, and publication. Each paper should be investigated for unfeasible features of the governance, methodology, execution, results, and reporting of the study. Pairwise comparison of baseline and outcome tables between papers may reveal data duplication or unfeasibly large differences between baseline characteristics in similar studies. Assessment of baseline characteristics from multiple randomized trials using Carlisle’s method can determine whether the data are consistent with a properly executed randomization process, as can checking whether reported baseline characteristics follow expected patterns for random variables such as Benford’s law. If serious concerns are raised, a more thorough investigation should be performed by journals, publishers, and institutions.</div></div><div><h3>Conclusion</h3><div>These methods provide a systematic and reproducible way to assess the collected work of an author or group of authors.</div></div><div><h3>Plain Language Summary</h3><div>It is increasingly accepted that papers reporting on clinical studies may contain fraudulent or falsified data, often multiple papers by a single author or author group. Based on our experience assessing the research integrity of collections of papers by one author or author group, we present an approach to these investigations that combines published statistical methods with pragmatic assessment of study feasibility. This will help journals and publishers better identify groups of potentially untrustworthy studies.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111603"},"PeriodicalIF":7.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research participation effects and where to find them: a systematic review of studies on alcohol","authors":"Katarina Ulfsdotter Gunnarsson,&nbsp;Elizabeth S. Collier,&nbsp;Marcus Bendtsen","doi":"10.1016/j.jclinepi.2025.111668","DOIUrl":"10.1016/j.jclinepi.2025.111668","url":null,"abstract":"<div><h3>Objectives</h3><div>The term ‘research participation effects’ (RPEs) is intended to capture features and artifacts of study design that may affect measured outcomes in ways that introduce bias into research findings, impacting inference and outcome validity. This systematic review aims to identify which RPEs have been studied in the context of alcohol research and provide an overview of estimates of RPEs on self-reported alcohol consumption.</div></div><div><h3>Study Design and Setting</h3><div>This systematic review summarizes the available evidence on RPEs in alcohol research.</div></div><div><h3>Results</h3><div>Twenty-seven reports were included in the review. The reports included randomized controlled trials (RCTs), studies-within-a-trial, between-subjects experiments, and qualitative investigations. A range of RPEs were addressed as follows: assessment reactivity (<em>N</em> = 15), being randomized to a waiting list control group (<em>N</em> = 3), the impact of obtaining informed consent (<em>N</em> = 2), experimentally induced social desirability (<em>N</em> = 3), and the Hawthorne effect, either specifically by name (<em>N</em> = 2, one quantitative, one qualitative) or described as general RPE presence (<em>N</em> = 2). The literature provided proportionally stronger evidence in favor of assessment reactivity and waiting list designs affecting alcohol outcomes, contrary to obtaining informed consent or inducing social desirability.</div></div><div><h3>Conclusion</h3><div>Variation in study quality, terminology, and outcome measures hinder comprehensive understanding and discussion of RPEs at present. Improved knowledge of RPEs and their potential long-term consequences in alcohol research, including a unified lexicon, would enhance trial design and improve the certainty of evidence in alcohol research.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"179 ","pages":"Article 111668"},"PeriodicalIF":7.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}