Clinical Epidemiology最新文献

{"title":"Association Between Pneumonia Risk and Anticholinergic Burden Among Patients with Different Frailty Levels.","authors":"Avery Shuei-He Yang, Hsin-Yu Fan Chiang, Daniel Hsiang-Te Tsai, Albert Tzu-Ming Chuang, Edward Chia-Cheng Lai","doi":"10.2147/CLEP.S524645","DOIUrl":"https://doi.org/10.2147/CLEP.S524645","url":null,"abstract":"<p><strong>Objective: </strong>We aimed to evaluate the association between recent increase in anticholinergic burden and risk of hospitalised pneumonia, taking frailty levels into consideration.</p><p><strong>Setting: </strong>We conducted a case-crossover study using data drawn from Taiwan's National Health Insurance Research Database.</p><p><strong>Participants: </strong>We enrolled patients aged over 65 years old who were hospitalised for pneumonia between 2011 and 2020. Exclusion criteria included prior diagnosis of ventilator dependency, pneumonia and immune dysfunction.</p><p><strong>Measurements: </strong>The observational period was divided into a hazard period, a washout period and one of four reference periods, based on the 30-day interval before the admission. We calculated the anticholinergic cognitive burden (ACB) scale for the hazard period and one randomly selected reference period. Using a multimorbidity frailty index we classified patients into four groups (ie, fit, mildly frail, moderately frail and very frail).</p><p><strong>Statistical analysis: </strong>We used conditional logistic regression to evaluate the risk of pneumonia by comparing the anticholinergic burden between the hazard window and the randomly selected reference window and conducted sensitivity analyses based on case-time control and case-case-time control analysis to examine the robustness of the findings.</p><p><strong>Results: </strong>The fit group included 188,740 patients, followed by 133,038, 61,805 and 18,198 patients for the mildly, moderately and very frail groups, respectively. Each single point increase in ACB scale was associated with a pneumonia risk increase by 1.35 (95% CI: 1.34-1.35), 1.24 (95% CI: 1.24-1.24), 1.18 (95% CI: 1.17-1.18) and 1.12 (95% CI: 1.11-1.13) times in the fit and mildly, moderately and very frail groups, respectively. The results of the case-time control and case-case-time control analyses remained consistent with the main analysis.</p><p><strong>Conclusion: </strong>Our study confirmed the association between recently elevated ACB and the risk of hospitalised pneumonia. Even in the less frail, exposure to anticholinergic drugs warrants close monitoring for pneumonia.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"787-796"},"PeriodicalIF":3.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145231494","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":"Sex Differences in Antihypertensive Medications and PTSD Incidence.","authors":"Sophie M Selbe, Péter Szentkúti, Travis C Evans, Timothy L Lash, Jennifer A Sumner, Jaimie L Gradus","doi":"10.2147/CLEP.S533048","DOIUrl":"10.2147/CLEP.S533048","url":null,"abstract":"<p><strong>Purpose: </strong>Evidence suggests there may be a protective association between some antihypertensive medications and posttraumatic stress disorder (PTSD) incidence, but few samples are large enough to examine sex differences in these associations.</p><p><strong>Methods: </strong>Data came from a trauma cohort established from the Danish national registries from 1994 to 2016. All cohort members experienced at least one of the seven potentially traumatic events (PTE). Those exposed redeemed prescriptions for antihypertensive medications (beta blockers, angiotensin II receptor blockers [ARBs], angiotensin-converting enzyme inhibitors [ACE-Is], and calcium channel blockers) within 60 days prior to PTE. For the unexposed group, three persons who never redeemed an antihypertensive medication prescription were matched to each exposed person on age, sex, and time of trauma. The outcome was incident PTSD over 22 years of follow-up (average follow-up time was 5-6 years). We conducted descriptive analyses followed by Cox proportional hazards regression adjusted for marital status, income, trauma group, Charlson Comorbidity Index score before the PTE, and comedication use of statins, non-steroidal anti-inflammatory drugs, and antidepressants to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Analyses were sex-stratified.</p><p><strong>Results: </strong>We observed evidence of a protective association between calcium channel blockers and the development of PTSD for females (HR = 0.79; 95% CI = 0.29, 2.2) and males (HR = 0.49; 95% CI = 0.22, 1.1). For females, the adjusted association between ARBs and PTSD was 0.47 (95% CI = 0.11, 2.1); for males, the adjusted association was 1.4 (95% CI = 0.50, 3.6). A slight protective effect was also observed for beta-blockers among males, while these associations closer to the null were observed for females. For both sexes, associations with ACEs were closer to the null.</p><p><strong>Conclusion: </strong>These results suggest possible sex differences in the potentially protective effects of antihypertensive medications on the development of PTSD, although imprecision in measurement indicates results should be interpreted with caution.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"779-786"},"PeriodicalIF":3.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12450376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145124273","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":"Post-Marketing Safety Concerns with Efgartigimod alfa: A Pharmacovigilance Analysis Based on the Food and Drug Administration Adverse Event Reporting System Database.","authors":"Jinlong Huang, Hanyun Ye, Jingyang Lin, Dan Luo, Ping Huang, Xiaochun Zheng","doi":"10.2147/CLEP.S514738","DOIUrl":"10.2147/CLEP.S514738","url":null,"abstract":"<p><strong>Aim: </strong>Efgartigimod alfa (EA) is a novel US Food and Drug Administration (FDA) approved neonatal Fc receptor-targeting drug; however, its real-world adverse event (AE) profile remains underexplored.</p><p><strong>Methods: </strong>AE reports primarily related to EA were retrieved from the US FDA Adverse Event Reporting System database for the fourth quarter of 2021 to the third quarter of 2024. Disproportionality analysis using Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker algorithms was employed to detect signals of AEs.</p><p><strong>Results: </strong>Our study processed 3,182 AE reports related to EA, revealing 57 signals that met the criteria of the ROR, PRR, Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker algorithms across 14 system organ classes. Notably, the most significant signal in the System Organ Class was \"Surgical and medical procedures\", whereas the most significant signal in Preferred Term was \"Bulbar Palsy\". Some unexpected over-the-counter AEs, including falls, choking, sepsis, nephrolithiasis, and atrial fibrillation, were also observed. The median onset time of EA-related AEs was 101.5 d (interquartile range 27-260). The AE risk model associated with EA should be referred to as \"early failure\", with the likelihood of AEs decreasing over time.</p><p><strong>Conclusion: </strong>This study highlights the potential AEs and risks associated with the clinical use of EA; the analysis provides significant evidence regarding the clinical safety of EA.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"765-778"},"PeriodicalIF":3.2,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12449886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145112132","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":"Systematic Review and Development of Recommended Code Lists to Identify Smoking and Vaping Status in Electronic Health Records (EHR).","authors":"Rong Ding, Sarah Cook, Philip W Stone, Dharun Srirathan, Yashwin Shyam, Ruhan Anand, Palaniappa Sudharshan, Jennifer K Quint","doi":"10.2147/CLEP.S529563","DOIUrl":"10.2147/CLEP.S529563","url":null,"abstract":"<p><strong>Introduction: </strong>Vaping and smoking are important health behaviours associated with many diseases. Evaluating the association of smoking and vaping with diseases using electronic health record (EHR) data requires accurate codelists to determine smoking and vaping status. However, codelists used in studies are not always published or consistent between studies. It is important to develop standard codelists for use in future studies, and transparency is required to ensure consistency and standardization.</p><p><strong>Purpose: </strong>To provide an overview of the codes used in both peer-reviewed scientific literature and codelist repositories to identify smoking and vaping status in EHRs and derive a recommended codelist for use in EHRs to identify smoking and vaping status.</p><p><strong>Methods: </strong>Publications (MEDLINE, Embase, and Scopus) and codelist repositories (LSHTM Data Compass, OpenCodelists, and the HDR UK Phenotype Library) were searched from January 2010 to April 2024. All publications or codelist repositories with codes referring to smoking/vaping status were included in this review (search terms are further addressed in Supplementary Table 1). All codes were extracted to review the frequency and consistency between studies.</p><p><strong>Results: </strong>There were 100 codelists across different coding systems: 55 codelists from publications and 45 codelists from codelist repository entries. For vaping status, there were 23 codelists identified, 7 from publications, and 16 from codelist repositories. Only 10% of publications included codelists. A limited number of ICD codes were used, and more were reported using the Read or SNOMED CT codes. The codelists we subsequently developed were based on those found in the review.</p><p><strong>Conclusion: </strong>Very few studies have reported the use of codelists despite smoking status being a widely used variable in many publications, and vaping status is increasing. Using the information from the review, we derived codelists for smoking and vaping using a transparent methodology that can be used in future studies.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"753-764"},"PeriodicalIF":3.2,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12433228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145063473","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":"Positive Predictive Value of ICD-10 Codes for Identifying Hypocalcemia in Women with Postmenopausal Osteoporosis in Swedish Patient Register: A Validation Study.","authors":"Anders Kjellman, Min Kim, Per-Olof Lundgren, Tomas Thiel, Anna Thor, Helena Thulin, David Hägg, Vera Ehrenstein","doi":"10.2147/CLEP.S525181","DOIUrl":"10.2147/CLEP.S525181","url":null,"abstract":"<p><strong>Purpose: </strong>To estimate the positive predictive value (PPV) of case ascertainment algorithm for hypocalcemia leading to hospitalization or emergency visit in the Swedish National Patient Register among women with postmenopausal osteoporosis (PMO) treated with antiresorptive agents. This was a regulator-requested validation study to support a multidatabase postauthorisation safety study (PASS) of antiresorptive treatment.</p><p><strong>Methods: </strong>The Swedish part of the PASS was based on data from Swedish population registries. Potential cases of hypocalcemia, identified among women with PMO, included in the PASS in 2010-2016, were defined based on non-specific International Classification of Diseases, 10th Revision (ICD-10) codes for disorders of calcium metabolism at hospitalization or emergency visit, as recorded in the Swedish Patient Register through 2018. Presence of hypocalcemia among the potential cases was confirmed using a standardized abstraction of medical charts. PPV was estimated as a measure of validity.</p><p><strong>Results: </strong>There were 164 potential cases of hypocalcemia, of which 121 had medical charts with sufficient information available. Among these 121 cases, 19 had confirmed hypocalcemia, PPV 15.7% (95% confidence interval: 10.0 to 23.0).</p><p><strong>Conclusion: </strong>The case-defining algorithm based on the non-specific ICD-10 codes had a low PPV. Reliance on the algorithm may bias results of epidemiologic studies relying it. Limitations include non-response and low precision of some PPV estimates.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"747-752"},"PeriodicalIF":3.2,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12413818/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145013951","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":"Existing Data Sources in Clinical Epidemiology: The Danish Prehospital Medical Record System.","authors":"Oscar Rosenkrantz, Christian S Benson, Tim Alex Lindskou, Cecilia H Fuglsang, Lars Pedersen, Søren Mikkelsen, Helle Collatz Christensen, Erika Frischknecht Christensen, Jacob Steinmetz, Henrik Toft Sørensen","doi":"10.2147/CLEP.S524197","DOIUrl":"10.2147/CLEP.S524197","url":null,"abstract":"<p><strong>Background: </strong>The Danish Prehospital Medical Record (DPMR) represents a pioneering nationwide electronic prehospital medical record system. While routinely collected data from the DPMR are increasingly used for research, a comprehensive description of its system and content is needed.</p><p><strong>Objective: </strong>To provide an overview of the DPMR as a tool for research, including its structure, variables, and current volume of records.</p><p><strong>Methods: </strong>We examined the DPMR's history, data structure, content, and data usage. We also analyzed aggregated DPMR data from 2016 to 2023 for selected key variables. Further, we searched MEDLINE to identify studies utilizing this data source in the past decade.</p><p><strong>Results: </strong>Since 2016, the DPMR system has grown to include 1.8 million unique prehospital patients with over 6 million associated patient contacts. For each patient contact, the DPMR compiles information on the emergency medical call (dispatch criteria, level of urgency, and pre-arrival treatment), characteristics of the incident (patient examination, treatment, response time, on-scene time, and transport time), emergency medical services units (ambulances, rapid response vehicles with paramedics, anesthesiologists in ground-based mobile emergency care units and/or helicopters, or patient transports without treatment capability), and extensive patient-related data. The system currently encompasses 528 variables, standardized across all emergency medical services units. There are a limited number of studies on the data quality of the system and the proportion of patients with missing civil registration numbers has varied between approximately 5% and 9%, which should be taken into account when using it for research.</p><p><strong>Conclusion: </strong>The DPMR is growing in importance as a research tool in Denmark. It provides nationwide patient-related and logistical prehospital data going back to 2016, enabling linkage with national registries for outcome research.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"735-745"},"PeriodicalIF":3.2,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12407003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144999869","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":"Prevalence and Data-Driven Exploration of Pre-Diagnostic Symptoms and Features of Gilbert's Syndrome in the UK Primary Care Population.","authors":"Rini S S Veeravalli, Laura J Horsfall, Kenan Direk, Irene Petersen","doi":"10.2147/CLEP.S520589","DOIUrl":"10.2147/CLEP.S520589","url":null,"abstract":"<p><strong>Background: </strong>Gilbert's syndrome (GS) is a common genetic disorder marked by elevated bilirubin levels due to UGT1A1 enzyme deficiency. While jaundice and some adverse drug reactions are the primary recognised clinical features, individuals with GS frequently report non-specific symptoms like fatigue, brain fog, and abdominal pain. This study investigates the symptoms and diagnostic triggers of GS using UK primary care electronic health records.</p><p><strong>Methods: </strong>We analysed data from the IQVIA Medical Research Database, covering over 11 million active UK patients. Individuals with a recorded GS diagnosis were identified and their sociodemographic profiles described. Using a nested case-control design, we applied machine learning-based feature selection to pinpoint key clinical features recorded up to five years before diagnosis. These features were then examined longitudinally by sex to distinguish persistent symptoms from short-term diagnostic triggers.</p><p><strong>Results: </strong>The estimated UK prevalence of GS was 180.4 per 100,000 (95% CI: 174.4-186.6), with diagnoses more common in men, peaking around age 35, and more frequent in areas of least social deprivation. Among 9,240 GS cases and 150,846 controls, machine learning identified key diagnostic themes including jaundice, abnormal liver function tests, abdominal pain, fatigue, bowel changes, and sleep disturbances. While most of these features appeared primarily in the year prior to diagnosis, only abdominal pain and fatigue were consistently more common in GS cases up to five years before diagnosis.</p><p><strong>Conclusion: </strong>Our findings highlight both expected and novel GS diagnostic triggers. While many features likely reflect known symptomology or incidental detection via routine testing, the persistent presence of fatigue and abdominal pain suggests they may be under-recognised symptoms of GS. These findings warrant further investigation, and the data-driven approach used here may help uncover early signs of other underdiagnosed genetic conditions.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"721-733"},"PeriodicalIF":3.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12402429/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144991578","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":"Predictors, Healthcare Utilization and Costs Related to Short-Term Stays in Patients with COPD: A Registry-Based Analysis in Norway.","authors":"Tron Anders Moger, Jon Helgheim Holte, Olav Amundsen, Silje Bjørnsen Haavaag, Øystein Døhl, Line Kildal Bragstad, Ragnhild Hellesø, Trond Tjerbo, Nina Køpke Vøllestad","doi":"10.2147/CLEP.S521958","DOIUrl":"10.2147/CLEP.S521958","url":null,"abstract":"<p><strong>Background: </strong>Chronic obstructive pulmonary disease (COPD) incurs significant healthcare costs, often accompanied by multimorbidity. Advanced patients may need short-term stays for rehabilitation, treatment, or respite to maintain home living.</p><p><strong>Aim: </strong>To identify predictors for a first short-term stay and study the healthcare utilization and costs compared with similar patients without a short-term stay.</p><p><strong>Patients and methods: </strong>Data on COPD patients in the cities Oslo and Trondheim 2010-2019 and including information on specialist, primary and long-term care, diagnoses, sociodemographics and -economics were collected from national and municipal registries, resulting in a sample of 24,613 patients. Using discrete time survival models, we identified predictors for a short-term stay. We described the costs before and after admission, and the duration of living at home, compared to non-recipients matched on age, comorbidities and healthcare use.</p><p><strong>Results: </strong>Depression, anxiety, mental disorders, alcoholism, prior hospitalization and reception of home care were associated with higher odds of short-term stays. One to two GP visits for respiratory diseases, being in the top quartile for GP visits for non-respiratory diseases, visits to specialists, and physiotherapist visits for non-respiratory issues were significantly associated with lower odds of short-term institutional stay. Patients admitted to short-term stays incurred markedly higher costs both in the year before admission and during subsequent years compared to matched non-recipients, primarily due to increased use of inpatient and home care services.</p><p><strong>Conclusion: </strong>Prior receipt of home care, unlike standard outpatient services, was linked to a higher likelihood of short-term stays. This suggests that some outpatient services may delay the need for such stays, or that patients already in municipal services are more readily admitted. Additionally, patients with psychosocial issues may have greater care needs, indicating that resource allocation aligns with these needs. The findings suggest that by the time short-term stays are required, health deterioration has already become considerable.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"707-719"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12399859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144991654","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":"Using Restricted Mean Time Lost to Evaluate the Prognostic Effects on Locally Advanced Breast Cancer Considering Competing Risks.","authors":"Zhaojin Li, Di Liu, Yawen Hou, Zheng Chen","doi":"10.2147/CLEP.S521309","DOIUrl":"10.2147/CLEP.S521309","url":null,"abstract":"<p><strong>Background: </strong>In the presence of competing risks, when the baseline risk is unclear, if only the sub-distribution hazard ratio (SHR) is reported in the results, which is related to the cumulative incidence function, the survival disparity of events of interest between groups cannot be clarified. In contrast, the difference in restricted mean time lost (RMTLd), which is the difference in the areas under the cumulative incidence between two groups, can well compensate for the deficiencies of SHR and explain the effects on a time scale, facilitating clinical interpretation and communication.</p><p><strong>Methods: </strong>The Surveillance, Epidemiology, and End Results (SEER) database was used to collect information on female patients with locally advanced breast cancer diagnosed between 2010 and 2015. The prognostic factors of breast cancer death were evaluated considering competing risk. Univariable and multivariable analyses were conducted to get SHR and RMTLd.</p><p><strong>Results: </strong>SHR can indicate the direction of prognostic factors, while RMTLd can quantify prognostic effects and provide time-scale interpretation. For instance, in adjuvant radiotherapy, the SHR showed a protective effect, which can be quantified as an average increase of 4.15 months in survival time.</p><p><strong>Discussion: </strong>In the presence of competing risks, the combined use of absolute measure RMTLd can more intuitively explain the prognostic effect, which is convenient for clinical practice and communication.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"693-705"},"PeriodicalIF":3.2,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12380099/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944952","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":"Mortality Outcomes in People with Lung Cancer with and without Type2 Diabetes: A Cohort Study in England.","authors":"Eseosa Grace Igbinosa, Bodini Dharmasekara, Jennifer K Quint, Sanjay Popat, Krishnan Bhaskaran, Daniel Morganstein, Sarah Cook","doi":"10.2147/CLEP.S498368","DOIUrl":"10.2147/CLEP.S498368","url":null,"abstract":"<p><strong>Introduction: </strong>The impact of type 2 diabetes (T2DM) on mortality following lung cancer diagnosis remains unclear, with conflicting evidence across studies. We aimed to assess differences in all-cause and cause-specific mortality between people with lung cancer with and without T2DM within a primary care population in England.</p><p><strong>Methods: </strong>The study population was 69,674 people with incident lung cancer within the Clinical Practice Research Datalink (CPRD) Aurum primary care database (2010-2022). The study exposure was T2DM at cancer diagnosis, and the outcomes were all-cause and cause-specific mortality (cancer, cardio-vascular, respiratory). Cox models were fitted for each outcome adjusting for age, gender, smoking status, body mass index, calendar year and socioeconomic status (Index of Multiple Deprivation).</p><p><strong>Results: </strong>After adjusting for age and gender, there was no evidence for a difference in all-cause mortality in people with T2DM compared with people without T2DM (IRR 0.98 95% CI 0.96, 1.01). After fully-adjusting for measured confounders, there was a small positive effect (IRR 1.07 95% CI 1.04, 1.09). After adjusting for age and gender, people with T2DM had lower rates of cancer-specific mortality compared to people without T2DM (IRR 0.96 95% CI 0.94, 0.98). However, after adjustment for all measured confounders there was a small positive association (IRR 1.05 95% CI 1.02, 1.07). In both age and gender adjusted and fully adjusted models people with T2DM had higher cardiovascular (fully adjusted HR 1.30 95% CI 1.15, 1.47) and respiratory disease mortality (fully adjusted HR 1.30 95% CI 1.15, 1.47).</p><p><strong>Conclusion: </strong>There was robust evidence that people with T2DM had higher cardiovascular and respiratory disease mortality following lung cancer diagnosis. The relationships between T2DM and all-cause and cancer-specific mortality were highly sensitive to adjustment for confounding. Differences in studies on approaches to confounding and levels of missing data may contribute to the mixed findings on this association in the literature.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"681-692"},"PeriodicalIF":3.4,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278945/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144682150","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}