BMC Medical Research Methodology最新文献

{"title":"Survival analysis of left-truncated and right-censored HIV data: comparison of Cox regression and alternative models.","authors":"Tuba Çakır, Yüksel Terzi","doi":"10.1186/s12874-026-02874-5","DOIUrl":"https://doi.org/10.1186/s12874-026-02874-5","url":null,"abstract":"<p><strong>Background: </strong>This study examined the impact of delayed entry in HIV cohorts by analyzing left-truncated and right-censored (LTRC) survival data from 69 HIV-positive male patients (24 deaths) followed at a tertiary infectious diseases center. The primary objective was to empirically compare commonly used survival models in estimating survival and identifying prognostic factors under LTRC conditions.</p><p><strong>Methods: </strong>Three LTRC-adapted modeling frameworks were applied with identical covariates: the semiparametric Cox proportional hazards model, accelerated failure time (AFT) models, and parametric proportional hazards models. Median survival time was estimated using Kaplan-Meier methods under both right-censoring-only and LTRC specifications to assess truncation-related differences. Hazard ratios (HRs) and 95% confidence intervals (CIs) were obtained from the LTRC-adjusted Cox model. Model performance was evaluated using information criteria (AIC, BIC, HQIC).</p><p><strong>Results: </strong>Ignoring left truncation substantially inflated median survival estimates (3,885 vs. 2,626 days). In the LTRC-adjusted Cox model, age (HR = 1.049, 95% CI: 1.011-1.089) and log-transformed HIV RNA (HR = 1.214, 95% CI: 1.055-1.400) were significant predictors, whereas CD4 count and comorbidity status were not. Among the evaluated models, the Cox model showed the lowest information criterion values within this dataset.</p><p><strong>Conclusions: </strong>Appropriate risk-set specification under left truncation is essential for reliable survival estimation in delayed-entry HIV cohorts. Within this empirical dataset, the LTRC-adapted Cox model showed favorable performance relative to AFT and parametric PH alternatives.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147855922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating search approaches for a network meta-analysis: a case study of Epistemonikos Database of Trials, CENTRAL, and other sources.","authors":"Irma Klerings, Andreea Dobrescu, Barbara Nussbaumer-Streit, Amin Sharifan, Camilla Neubauer-Bruckner, Gerald Gartlehner","doi":"10.1186/s12874-026-02870-9","DOIUrl":"https://doi.org/10.1186/s12874-026-02870-9","url":null,"abstract":"<p><strong>Background: </strong>MEDLINE, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), and reference lists are commonly used when searching randomized controlled trials (RCTs) for inclusion in a systematic review. Recently, a new database for RCTs, Epistemonikos Database of Trials (EDT), was launched in a pilot stage. This case study aimed to compare EDT, MEDLINE, Embase, CENTRAL, reference list checking, and database combinations for the identification of RCTs about pharmacological migraine treatments and to assess the impact of missed trials on network meta-analyses (NMA).</p><p><strong>Methods: </strong>We assessed the following: (1) the performance (recall, precision, number needed to read [NNR], F1- and F2-scores) of database searching, reference list checking, and database combinations compared to a relative recall reference standard, (2) the impact of differing search results on the findings of NMA (overall network estimates, certainty of evidence ratings) based on RCTs with low/moderate risk of bias, and (3) the suitability of EDT for systematic searching.</p><p><strong>Results: </strong>Recall was high for all assessed search approaches (98.3-99.4% for single-database searches without date limit, 99.4-100% for database combinations without date limit, and 93.3% for reference list checking of older systematic reviews combined with publication-date-limited database searching). However, NNR and F-Scores varied widely, ranging from an NNR of six and F2 of 0.5 for EDT alone to an NNR of 16 and F2 of 0.2 for the combination of reference list checking and database searching. Different search results led to similar network estimates and identical certainty-of-evidence assessments as the reference standard. While the search, export, and documentation functions of EDT were less sophisticated than other assessed databases/platforms, they were sufficient to conduct reproducible and comprehensive systematic searches.</p><p><strong>Conclusions: </strong>All search approaches we tested were acceptable for an NMA of pharmacological migraine treatments; high search recall led to similar NMA results. However, the associated number of references to be screened at title/abstract level differed greatly. Specialized RCT databases (CENTRAL, EDT) were more efficient in this regard than general healthcare research databases (MEDLINE, Embase). Additionally, the pilot version of EDT proved to be a promising cost-free option for RCT searching.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147833458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.","authors":"Luis Serviá, Mariona Badia, Neus Montserrat, Judit Vilanova, Gabriel Jiménez, Juan Antonio Llompart-Pou, Jesús Abelardo Barea-Mendoza, Mario Chico-Fernández, Javier Trujillano","doi":"10.1186/s12874-026-02792-6","DOIUrl":"https://doi.org/10.1186/s12874-026-02792-6","url":null,"abstract":"<p><strong>Background: </strong>In critically injured trauma patients, tools that stratify injury severity and estimate mortality are essential. Fuzzy logic (FL) enables the creation of accurate, interpretable models but requires decision rules, which can be generated using machine learning (ML) techniques like classification trees (CT). Our objective was to develop a hybrid model combining fuzzy logic and classification trees to estimate ICU mortality risk using only prehospital variables.</p><p><strong>Methods: </strong>We conducted a retrospective study using data from the Spanish Trauma ICU registry (RETRAUCI) from 2015 to 2022. Patients were randomly divided into derivation (DS) and validation sets (VS) (70:30). Candidate variables were those available in the prehospital phase. A hybrid model (HFL) was developed using a Fuzzy Inference System built with the 'FuzzyR' library in RStudio (v 2024.04.2) and the Mamdani method. CHAID (Chi-squared Automatic Interaction Detection) classification trees were used to derive the rules. The HFL's discrimination and calibration were compared with other scores: Revised Trauma Score (RTS); Glasgow Coma Scale, Age, and Arterial Pressure (GAP); Mechanism, Glasgow Coma Scale, Age, and Arterial Pressure (MGAP); Reverse shock index multiplied by Glasgow Coma Scale score (rSIG); and Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory Rate, and Systolic Blood Pressure (TRIAGE).</p><p><strong>Results: </strong>The study included 11,030 records, with 7,728 in the DS and 3,302 in the VS, and an overall mortality of 11.1%. Five variables were selected, ordered by importance: GCS, age, systolic blood pressure, respiratory rate, and heart rate. A total of 32 classification rules were generated. The HFL model achieved the highest accuracy in DS and VS, with AUROC of 0.87 (0.86-0.88) and 0.86 (0.83-0.88), and acceptable calibration with intercepts of -0.11 (-0.18 to -0.04) and - 0.19 (-0.32 to -0.06) and slopes of 0.99 (0.94-1.05) and 0.96 (0.83-0.88).</p><p><strong>Conclusions: </strong>Our hybrid model achieves accuracy comparable to commonly used models and provides clear clinical interpretation, with GCS and age as key variables.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147833451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When patients' voices aren't heard: estimands and statistical methods for handling missing patient-reported outcomes in oncology studies.","authors":"Emma C Martin, Rachael Lawrance, Alex Hind, Suzie Cro","doi":"10.1186/s12874-026-02862-9","DOIUrl":"https://doi.org/10.1186/s12874-026-02862-9","url":null,"abstract":"<p><strong>Introduction: </strong>Patient-reported outcomes (PROs) are integral to oncology clinical trials, yet missing data - especially due to intercurrent events (ICEs) of disease progression pose challenges for robust and interpretable analysis. While regulatory and best practice guidelines now emphasize the explicit definition of estimands, including strategies for handling ICEs, and supplementary analyses to examine their robustness, practical recommendations for their implementation in PRO analyses remain limited.</p><p><strong>Methods: </strong>We present a methodological framework for defining estimands and statistical analysis for a longitudinal change in a PRO confirmatory endpoint, including strategies for handling the main ICE of disease progression using a simulated clinical trial. We propose for the ICE of disease progression using either a hypothetical or treatment policy strategy for the main and supplementary analysis, and present implementation of two methods targeting a hypothetical approach and one method for treatment policy approach (implicit multiple imputation in a longitudinal model, a joint modelling of longitudinal PROs and time-to-progression, and multiple imputation using control-based imputation post progression).</p><p><strong>Results: </strong>We present the occurrence of ICEs and missing data and provide a tutorial for conducting analysis in the presence of disease progression using hypothetical and treatment policy strategies respectively. Despite the occurrence of disease progression events and other missing data, conducting supplementary analysis provided confidence in our overall interpretation for the simulated trial.</p><p><strong>Conclusions: </strong>Our recommendations provide practical guidance for specifying estimands, selecting statistical analysis methods, and interpreting PRO analyses in oncology trials with missing data. Accurately estimating the treatment effect on quality-of-life, in a way which is interpretable, is crucial to aid patients and other stakeholders when making treatment decisions.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of methods to handle missing values in a binary index test in a diagnostic accuracy study - a simulation study.","authors":"Dennis Juljugin, Katharina Stahlmann, Antonia Zapf","doi":"10.1186/s12874-026-02865-6","DOIUrl":"https://doi.org/10.1186/s12874-026-02865-6","url":null,"abstract":"<p><strong>Background: </strong>As there are no recommendations on handling missing values in a dichotomous index test of a diagnostic study, researchers often ignore missing values in the analysis or use simple methods. Thus, this simulation study compares selected methods regarding their performance of estimating sensitivity and specificity of a dichotomous index test with missing values.</p><p><strong>Methods: </strong>Data of a single-test diagnostic study were simulated including a dichotomous reference standard, a dichotomous index test and three dichotomous covariates. Following different proportions of missing values and missingness mechanisms, missing values were modeled in the index test. Additionally, the sample size, true sensitivity and specificity, and the prevalence of the target condition were varied in the data generation resulting in 729 scenarios. Seven methods were compared: complete case analysis, worst case scenario (WC), random hot deck, multiple imputation by chained equations (MICE), and three different product multinomial framework approaches.</p><p><strong>Results: </strong>Apart from WC, most methods are unbiased under missing completely at random (MCAR). Under missing at random (MAR), however, MICE clearly outperforms the other methods and is nearly unbiased while the other methods are considerably more biased. Additionally, MICE shows the best coverage probability for MCAR and MAR. If missing values are missing not at random (MNAR), all methods are substantially biased and show coverage probability that is too low.</p><p><strong>Conclusions: </strong>While most methods perform well when the proportion of missing values is small, especially under MCAR, MICE should be used when the proportion of missing values increases and the missing values are MAR. None of the tested methods seems to be suitable for MNAR.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"26 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13130772/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147811087","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":"An evaluation of variable selection methods in competing risks with one rare event: a simulation study.","authors":"Fatemeh Javanmardi, Zahra Shayan, Soheila Khodakarim, Amir Emami","doi":"10.1186/s12874-026-02859-4","DOIUrl":"https://doi.org/10.1186/s12874-026-02859-4","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147810955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating causal effects of rare treatments on binary outcomes: addressing sample size requirements and bias correction.","authors":"Ariful Islam Sanim, M Shafiqur Rahman, Mahbub A H M Latif","doi":"10.1186/s12874-026-02855-8","DOIUrl":"https://doi.org/10.1186/s12874-026-02855-8","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Choose-NI-metric: a shiny application for converting and comparing non-inferiority metrics in binary endpoint trials.","authors":"Wen Liu, Senmiao Ni, Ruyu Huang, Jingwei Wu, Hao Yu, Zhihang Peng, Zihang Zhong, Jianling Bai","doi":"10.1186/s12874-026-02860-x","DOIUrl":"https://doi.org/10.1186/s12874-026-02860-x","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A general sample size framework for developing or updating a predictive algorithm: with application to clinical prediction models.","authors":"Richard D Riley, Rebecca Whittle, Mohsen Sadatsafavi, Glen P Martin, Alexander Pate, Gary S Collins, Joie Ensor","doi":"10.1186/s12874-026-02856-7","DOIUrl":"https://doi.org/10.1186/s12874-026-02856-7","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multilingual analysis of public discourse on opioid and non-opioid analgesics through social media: a cross-sectional infodemiological study.","authors":"T Valades, A Ruiz-Iniesta, J Domingo-Espiñeira, J P Chart-Pascual, O Fraile-Martinez, C García-Montero, M Alvarez-Mon, I Morales, F Mora, J Quintero, M A Ortega, R Perez-Araluce, M A Alvarez-Mon","doi":"10.1186/s12874-026-02850-z","DOIUrl":"https://doi.org/10.1186/s12874-026-02850-z","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}