BMC Medical Research Methodology最新文献

{"title":"Feasibility of using real-world data to emulate substance use disorder clinical trials: a cross-sectional study.","authors":"Guneet S Janda, Molly Moore Jeffery, Reshma Ramachandran, Joseph S Ross, Joshua D Wallach","doi":"10.1186/s12874-024-02307-1","DOIUrl":"10.1186/s12874-024-02307-1","url":null,"abstract":"<p><strong>Introduction: </strong>Real-world evidence is receiving considerable attention as a way to evaluate the efficacy and safety of medical products for substance use disorders (SUDs). However, the feasibility of using real-world data (RWD) to emulate clinical trials evaluating treatments for SUDs is uncertain. The aim of this study is to identify the number of clinical trials evaluating treatments for SUDs with reported results that could be feasibly emulated using observational data from contemporary insurance claims and/or electronic health record (EHR) data.</p><p><strong>Methods: </strong>In this cross-sectional study, all phase 2-4 trials evaluating treatments for SUDs registered on ClinicalTrials.gov with reported results were identified. Each trial was evaluated to determine if the indications, interventions, at least 80% of eligibility criteria, comparators, and primary end points could be ascertained using contemporarily available administrative claims and/or structured EHR data.</p><p><strong>Results: </strong>There were 272 SUD trials on ClinicalTrials.gov with reported results. Of these, when examining feasibility using contemporarily available administrative claims and/or structured EHR data, 262 (96.3%) had indications that were ascertainable; 194 (71.3%) had interventions that were ascertainable; 21 (7.7%) had at least 80% of eligibility criteria that were ascertainable; 17 (6.3%) had active comparators that were ascertainable; and 61 (22.4%) had primary end points that were ascertainable. In total, there were no trials for which all 5 characteristics were ascertainable using contemporarily available administrative claims and/or structured EHR data. When considering placebo comparators as ascertainable, there were 6 (2.2%) trials that had all 5 key characteristics classified as ascertainable from contemporarily available administrative claims and/or structured EHR data.</p><p><strong>Conclusions: </strong>No trials evaluating treatments for SUDs could be feasibly emulated using contemporarily available RWD, demonstrating a need for an increase in the resolution of data capture within a public health system to facilitate trial emulation.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11351457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142092237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing treatment effects with adjusted restricted mean time lost in observational competing risks data.","authors":"Haoning Shen, Chengfeng Zhang, Yu Song, Zhiheng Huang, Yanjie Wang, Yawen Hou, Zheng Chen","doi":"10.1186/s12874-024-02303-5","DOIUrl":"10.1186/s12874-024-02303-5","url":null,"abstract":"<p><strong>Background: </strong>According to long-term follow-up data of malignant tumor patients, assessing treatment effects requires careful consideration of competing risks. The commonly used cause-specific hazard ratio (CHR) and sub-distribution hazard ratio (SHR) are relative indicators and may present challenges in terms of proportional hazards assumption and clinical interpretation. Recently, the restricted mean time lost (RMTL) has been recommended as a supplementary measure for better clinical interpretation. Moreover, for observational study data in epidemiological and clinical settings, due to the influence of confounding factors, covariate adjustment is crucial for determining the causal effect of treatment.</p><p><strong>Methods: </strong>We construct an RMTL estimator after adjusting for covariates based on the inverse probability weighting method, and derive the variance to construct interval estimates based on the large sample properties. We use simulation studies to study the statistical performance of this estimator in various scenarios. In addition, we further consider the changes in treatment effects over time, constructing a dynamic RMTL difference curve and corresponding confidence bands for the curve.</p><p><strong>Results: </strong>The simulation results demonstrate that the adjusted RMTL estimator exhibits smaller biases compared with unadjusted RMTL and provides robust interval estimates in all scenarios. This method was applied to a real-world cervical cancer patient data, revealing improvements in the prognosis of patients with small cell carcinoma of the cervix. The results showed that the protective effect of surgery was significant only in the first 20 months, but the long-term effect was not obvious. Radiotherapy significantly improved patient outcomes during the follow-up period from 17 to 57 months, while radiotherapy combined with chemotherapy significantly improved patient outcomes throughout the entire period.</p><p><strong>Conclusions: </strong>We propose the approach that is easy to interpret and implement for assessing treatment effects in observational competing risk data.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11346024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142072026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mixed effects models but not t-tests or linear regression detect progression of apathy in Parkinson's disease over seven years in a cohort: a comparative analysis.","authors":"Anne-Marie Hanff, Rejko Krüger, Christopher McCrum, Christophe Ley","doi":"10.1186/s12874-024-02301-7","DOIUrl":"10.1186/s12874-024-02301-7","url":null,"abstract":"<p><strong>Introduction: </strong>While there is an interest in defining longitudinal change in people with chronic illness like Parkinson's disease (PD), statistical analysis of longitudinal data is not straightforward for clinical researchers. Here, we aim to demonstrate how the choice of statistical method may influence research outcomes, (e.g., progression in apathy), specifically the size of longitudinal effect estimates, in a cohort.</p><p><strong>Methods: </strong>In this retrospective longitudinal analysis of 802 people with typical Parkinson's disease in the Luxembourg Parkinson's study, we compared the mean apathy scores at visit 1 and visit 8 by means of the paired two-sided t-test. Additionally, we analysed the relationship between the visit numbers and the apathy score using linear regression and longitudinal two-level mixed effects models.</p><p><strong>Results: </strong>Mixed effects models were the only method able to detect progression of apathy over time. While the effects estimated for the group comparison and the linear regression were smaller with high p-values (+ 1.016/ 7 years, p = 0.107, -0.056/ 7 years, p = 0.897, respectively), effect estimates for the mixed effects models were positive with a very small p-value, indicating a significant increase in apathy symptoms by + 2.345/ 7 years (p < 0.001).</p><p><strong>Conclusion: </strong>The inappropriate use of paired t-tests and linear regression to analyse longitudinal data can lead to underpowered analyses and an underestimation of longitudinal change. While mixed effects models are not without limitations and need to be altered to model the time sequence between the exposure and the outcome, they are worth considering for longitudinal data analyses. In case this is not possible, limitations of the analytical approach need to be discussed and taken into account in the interpretation.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344430/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142054914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing transparency practices in dental randomized controlled trials.","authors":"Mayara Colpo Prado, Lara Dotto, Bernardo Agostini, Rafael Sarkis-Onofre","doi":"10.1186/s12874-024-02316-0","DOIUrl":"10.1186/s12874-024-02316-0","url":null,"abstract":"<p><strong>Background: </strong>To evaluate transparency practices in randomized controlled trials (RCTs) in dentistry.</p><p><strong>Methods: </strong>This meta-research study included RCTs in dentistry regardless of topic, methods, or level of detail reported. Only studies in English were considered. We searched PubMed for RCTs in dentistry published in English from December 31, 2016, to December 31, 2021. The screening was performed in duplicate, and data extracted included journal and author details, dental specialty, protocol registration, data and code sharing, conflict of interest declaration, and funding information. A descriptive analysis of the data was performed. We generated maps illustrating the reporting of transparency items by country of the corresponding author and a heat table reflecting reporting levels by dental specialty.</p><p><strong>Results: </strong>A total of 844 RCTs were included. Only 12.86% of studies reported any information about data and code sharing. Protocol registration was reported for 50.36% of RCTs. Conflict of interest (83.41%) and funding (71.68%) declarations were present in most studies. Conflicts of interest and funding were consistently reported regardless of country or specialty, while data and code sharing had a low level of reporting across specialties, as well as low dissemination across the world. Protocol registration exhibited considerable variability.</p><p><strong>Conclusions: </strong>Considering the importance of RCTs for evidence-based dentistry, it is crucial that everyone who participates in the scientific production and dissemination process actively and consistently promotes adherence to transparent scientific standards, particularly registration of protocols, and sharing of data and code.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142054913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User engagement in clinical trials of digital mental health interventions: a systematic review.","authors":"Jack Elkes, Suzie Cro, Rachel Batchelor, Siobhan O'Connor, Ly-Mee Yu, Lauren Bell, Victoria Harris, Jacqueline Sin, Victoria Cornelius","doi":"10.1186/s12874-024-02308-0","DOIUrl":"10.1186/s12874-024-02308-0","url":null,"abstract":"<p><strong>Introduction: </strong>Digital mental health interventions (DMHIs) overcome traditional barriers enabling wider access to mental health support and allowing individuals to manage their treatment. How individuals engage with DMHIs impacts the intervention effect. This review determined whether the impact of user engagement was assessed in the intervention effect in Randomised Controlled Trials (RCTs) evaluating DMHIs targeting common mental disorders (CMDs).</p><p><strong>Methods: </strong>This systematic review was registered on Prospero (CRD42021249503). RCTs published between 01/01/2016 and 17/09/2021 were included if evaluated DMHIs were delivered by app or website; targeted patients with a CMD without non-CMD comorbidities (e.g., diabetes); and were self-guided. Databases searched: Medline; PsycInfo; Embase; and CENTRAL. All data was double extracted. A meta-analysis compared intervention effect estimates when accounting for engagement and when engagement was ignored.</p><p><strong>Results: </strong>We identified 184 articles randomising 43,529 participants. Interventions were delivered predominantly via websites (145, 78.8%) and 140 (76.1%) articles reported engagement data. All primary analyses adopted treatment policy strategies, ignoring engagement levels. Only 19 (10.3%) articles provided additional intervention effect estimates accounting for user engagement: 2 (10.5%) conducted a complier-average-causal effect (CACE) analysis (principal stratum strategy) and 17 (89.5%) used a less-preferred per-protocol (PP) population excluding individuals failing to meet engagement criteria (estimand strategies unclear). Meta-analysis for PP estimates, when accounting for user engagement, changed the standardised effect to -0.18 95% CI (-0.32, -0.04) from - 0.14 95% CI (-0.24, -0.03) and sample sizes reduced by 33% decreasing precision, whereas meta-analysis for CACE estimates were - 0.19 95% CI (-0.42, 0.03) from - 0.16 95% CI (-0.38, 0.06) with no sample size decrease and less impact on precision. DISCUSSION: Many articles report user engagement metrics but few assessed the impact on the intervention effect missing opportunities to answer important patient centred questions for how well DMHIs work for engaged users. Defining engagement in this area is complex, more research is needed to obtain ways to categorise this into groups. However, the majority that considered engagement in analysis used approaches most likely to induce bias.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344322/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142054915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualizing and diagnosing spillover within randomized concurrent controlled trials through the application of diagnostic test assessment methods.","authors":"James C Hurley","doi":"10.1186/s12874-024-02296-1","DOIUrl":"10.1186/s12874-024-02296-1","url":null,"abstract":"<p><strong>Background: </strong>Spillover of effect, whether positive or negative, from intervention to control group patients invalidates the Stable Unit Treatment Variable Assumption (SUTVA). SUTVA is critical to valid causal inference from randomized concurrent controlled trials (RCCT). Spillover of infection prevention is an important population level effect mediating herd immunity. This herd effect, being additional to any individual level effect, is subsumed within the overall effect size (ES) estimate derived by contrast-based techniques from RCCT's. This herd effect would manifest only as increased dispersion among the control group infection incidence rates above background.</p><p><strong>Methods and results: </strong>The objective here is to explore aspects of spillover and how this might be visualized and diagnosed. I use, for illustration, data from 190 RCCT's abstracted in 13 Cochrane reviews of various antimicrobial versus non-antimicrobial based interventions to prevent pneumonia in ICU patients. Spillover has long been postulated in this context. Arm-based techniques enable three approaches to identify increased dispersion, not available from contrast-based techniques, which enable the diagnosis of spillover within antimicrobial versus non-antimicrobial based infection prevention RCCT's. These three approaches are benchmarking the pneumonia incidence rates versus a clinically relevant range, comparing the dispersion in pneumonia incidence among the control versus the intervention groups and thirdly, visualizing the incidence dispersion within summary receiver operator characteristic (SROC) plots. By these criteria there is harmful spillover effects to concurrent control group patients.</p><p><strong>Conclusions: </strong>Arm-based versus contrast-based techniques lead to contrary inferences from the aggregated RCCT's of antimicrobial based interventions despite similar summary ES estimates. Moreover, the inferred relationship between underlying control group risk and ES is 'flipped'.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11328391/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141995296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the evaluation of synthetic longitudinal electronic health records.","authors":"Jim L Achterberg, Marcel R Haas, Marco R Spruit","doi":"10.1186/s12874-024-02304-4","DOIUrl":"10.1186/s12874-024-02304-4","url":null,"abstract":"<p><strong>Background: </strong>Synthetic Electronic Health Records (EHRs) are becoming increasingly popular as a privacy enhancing technology. However, for longitudinal EHRs specifically, little research has been done into how to properly evaluate synthetically generated samples. In this article, we provide a discussion on existing methods and recommendations when evaluating the quality of synthetic longitudinal EHRs.</p><p><strong>Methods: </strong>We recommend to assess synthetic EHR quality through similarity to real EHRs in low-dimensional projections, accuracy of a classifier discriminating synthetic from real samples, performance of synthetic versus real trained algorithms in clinical tasks, and privacy risk through risk of attribute inference. For each metric we discuss strengths and weaknesses, next to showing how it can be applied on a longitudinal dataset.</p><p><strong>Results: </strong>To support the discussion on evaluation metrics, we apply discussed metrics on a dataset of synthetic EHRs generated from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) repository.</p><p><strong>Conclusions: </strong>The discussion on evaluation metrics provide guidance for researchers on how to use and interpret different metrics when evaluating the quality of synthetic longitudinal EHRs.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11323671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141981631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deeper consideration of sex/gender in quantitative health research: a checklist for incorporating multidimensionality, variety, embodiment, and intersectionality throughout the whole research process.","authors":"Christina Hartig, Sophie Horstmann, Katharina Jacke, Ute Kraus, Lisa Dandolo, Alexandra Schneider, Kerstin Palm, Gabriele Bolte","doi":"10.1186/s12874-024-02258-7","DOIUrl":"10.1186/s12874-024-02258-7","url":null,"abstract":"<p><strong>Background: </strong>There is a growing awareness of the need to adequately integrate sex and gender into health-related research. Although it is widely known that the entangled dimensions sex/gender are not comprehensively considered in most studies to date, current publications of conceptual considerations and guidelines often only give recommendations for certain stages of the research process and - to the best of our knowledge - there is a lack of a detailed guidance that accompanies each step of the entire research process. The interdisciplinary project \"Integrating gender into environmental health research\" (INGER) aimed to fill this gap by developing a comprehensive checklist that encourages sex/gender transformative research at all stages of the research process of quantitative health research. In the long term this contributes to a more sex/gender-equitable research.</p><p><strong>Methods: </strong>The checklist builds on current guidelines on sex/gender in health-related research. Starting from important key documents, publications from disciplines involved in INGER were collected. Furthermore, we used a snowball method to include further relevant titles. The identification of relevant publications was continued until saturation was reached. 55 relevant publications published between 2000 and 2021 were identified, assessed, summarised and included in the developed checklist. After noticing that most publications did not cover every step of the research process and often considered sex/gender in a binary way, the recommendations were modified and enriched based on the authors' expertise to cover every research step and to add further categories to the binary sex/gender categories.</p><p><strong>Results: </strong>The checklist comprises 67 items in 15 sections for integrating sex/gender in quantitative health-related research and addresses aspects of the whole research process of planning, implementing and analysing quantitative health studies as well as aspects of appropriate language, communication of results to the scientific community and the public, and research team composition.</p><p><strong>Conclusion: </strong>The developed comprehensive checklist goes beyond a binary consideration of sex/gender and thus enables sex/gender-transformative research. Although the project INGER focused on environmental health research, no aspects that were specific to this research area were identified in the checklist. The resulting comprehensive checklist can therefore be used in different quantitative health-related research fields.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11316289/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141911624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"School-level intra-cluster correlation coefficients and autocorrelations for children's accelerometer-measured physical activity in England by age and gender.","authors":"Ruth Salway, Russell Jago, Frank de Vocht, Danielle House, Alice Porter, Robert Walker, Ruth Kipping, Christopher G Owen, Mohammed T Hudda, Kate Northstone, Esther van Sluijs","doi":"10.1186/s12874-024-02290-7","DOIUrl":"10.1186/s12874-024-02290-7","url":null,"abstract":"<p><strong>Background: </strong>Randomised, cluster-based study designs in schools are commonly used to evaluate children's physical activity interventions. Sample size estimation relies on accurate estimation of the intra-cluster correlation coefficient (ICC), but published estimates, especially using accelerometry-measured physical activity, are few and vary depending on physical activity outcome and participant age. Less commonly-used cluster-based designs, such as stepped wedge designs, also need to account for correlations over time, e.g. cluster autocorrelation (CAC) and individual autocorrelation (IAC), but no estimates are currently available. This paper estimates the school-level ICC, CAC and IAC for England children's accelerometer-measured physical activity outcomes by age group and gender, to inform the design of future school-based cluster trials.</p><p><strong>Methods: </strong>Data were pooled from seven large English datasets of accelerometer-measured physical activity data between 2002-18 (> 13,500 pupils, 540 primary and secondary schools). Linear mixed effect models estimated ICCs for weekday and whole week for minutes spent in moderate-to-vigorous physical activity (MVPA) and being sedentary for different age groups, stratified by gender. The CAC (1,252 schools) and IAC (34,923 pupils) were estimated by length of follow-up from pooled longitudinal data.</p><p><strong>Results: </strong>School-level ICCs for weekday MVPA were higher in primary schools (from 0.07 (95% CI: 0.05, 0.10) to 0.08 (95% CI: 0.06, 0.11)) compared to secondary (from 0.04 (95% CI: 0.03, 0.07) to (95% CI: 0.04, 0.10)). Girls' ICCs were similar for primary and secondary schools, but boys' were lower in secondary. For all ages, combined the CAC was 0.60 (95% CI: 0.44-0.72), and the IAC was 0.46 (95% CI: 0.42-0.49), irrespective of follow-up time. Estimates were higher for MVPA vs sedentary time, and for weekdays vs the whole week.</p><p><strong>Conclusions: </strong>Adequately powered studies are important to evidence effective physical activity strategies. Our estimates of the ICC, CAC and IAC may be used to plan future school-based physical activity evaluations and were fairly consistent across a range of ages and settings, suggesting that results may be applied to other high income countries with similar school physical activity provision. It is important to use estimates appropriate to the study design, and that match the intended study population as closely as possible.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11313128/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141911625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of effective reproduction number of infectious disease individuals based on spatiotemporal discriminant search model: take hand-foot-mouth disease as an example.","authors":"Linyi Wang, Yue Wu, Yin He, Yu Zhang","doi":"10.1186/s12874-024-02282-7","DOIUrl":"10.1186/s12874-024-02282-7","url":null,"abstract":"<p><strong>Objective: </strong>In order to facilitate the tracing of infectious diseases in a small area and to effectively carry out disease control and epidemiological investigations, this research proposes a novel spatiotemporal model to estimate effective reproduction number(Re)for infectious diseases, based on the fundamental concept of contact tracing.</p><p><strong>Methods: </strong>This study utilizes the incidence of hand, foot, and mouth disease (HFMD) among children in Bishan District, Chongqing, China from 2015 to 2019. The study incorporates the epidemiological characteristics of HFMD and aims to construct a Spatiotemporal Correlation Discrimination of HFMD. Utilizing ARC ENGINE and C# programming for the creation of a spatio-temporal database dedicated to HFMD to facilitate data collection and analysis. The scientific validity of the proposed method was verified by comparing the effective reproduction number obtained by the traditional SEIR model.</p><p><strong>Results: </strong>We have ascertained the optimal search radius for the spatiotemporal search model to be 1.5 km. Upon analyzing the resulting Re values, which range from 1.14 to 4.75, we observe a skewed distribution pattern from 2015 to 2019. The median and quartile Re value recorded is 2.42 (1.98, 2.72). Except for 2018, the similarity coefficient r of the years 2015, 2016, 2017, and 2019 were all close to 1, and p <0.05 in the comparison of the two models, indicating that the Re values obtained by using the search model and the traditional SEIR model are correlated and closely related. The results exhibited similarity between the Re curves of both models and the epidemiological characteristics of HFMD. Finally, we illustrated the regional distribution of Re values obtained by the search model at various time intervals on Geographic Information System (GIS) maps which highlighted variations in the incidence of diseases across different communities, neighborhoods, and even smaller areas.</p><p><strong>Conclusion: </strong>The model comprehensively considers both temporal variation and spatial heterogeneity in disease transmission and accounts for each individual's distinct time of onset and spatial location. This proposed method differs significantly from existing mathematical models used for estimating Re in that it is founded on reasonable scientific assumptions and computer algorithms programming that take into account real-world spatiotemporal factors. It is particularly well-suited for estimating the Re of infectious diseases in relatively stable mobile populations within small geographical areas.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536686/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141905914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}