scholarly journals Propensity score methods to control for confounding in observational cohort studies: a statistical primer and application to endoscopy research

2019 ◽  
Vol 90 (3) ◽  
pp. 360-369 ◽  
Author(s):  
Jeff Y. Yang ◽  
Michael Webster-Clark ◽  
Jennifer L. Lund ◽  
Robert S. Sandler ◽  
Evan S. Dellon ◽  
...  
Keyword(s):  
Propensity Score ◽  
Cohort Studies ◽  
Propensity Score Methods ◽  
Observational Cohort

scholarly journals Implementing an automated monitoring process in a digital, longitudinal observational cohort study

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Lisa Lindner ◽  
Anja Weiß ◽  
Andreas Reich ◽  
Siegfried Kindler ◽  
Frank Behrens ◽  
...  
Keyword(s):  
Cohort Studies ◽  
Data Quality ◽  
Missing Values ◽  
Randomized Clinical Trials ◽  
Cost Effective ◽  
Observational Research ◽  
Research Centre ◽  
Automated Monitoring ◽  
Monitoring Process ◽  
Observational Cohort

Abstract Background Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research. Methods An automated digital monitoring system for cohort studies developed by the German Rheumatism Research Centre (DRFZ) was tested within the disease register RABBIT-SpA, a longitudinal observational study including patients with axial spondyloarthritis and psoriatic arthritis. Physicians and patients complete electronic case report forms (eCRF) twice a year for up to 10 years. Automatic plausibility checks were implemented to verify all data after entry into the eCRF. To identify conflicts that cannot be found by this approach, all possible conflicts were compiled into a catalog. This “conflict catalog” was used to create queries, which are displayed as part of the eCRF. The proportion of queried eCRFs and responses were analyzed by descriptive methods. For the analysis of responses, the type of conflict was assigned to either a single conflict only (affecting individual items) or a conflict that required the entire eCRF to be queried. Results Data from 1883 patients was analyzed. A total of n = 3145 eCRFs submitted between baseline (T0) and T3 (12 months) had conflicts (40–64%). Fifty-six to 100% of the queries regarding eCRFs that were completely missing were answered. A mean of 1.4 to 2.4 single conflicts occurred per eCRF, of which 59–69% were answered. The most common missing values were CRP, ESR, Schober’s test, data on systemic glucocorticoid therapy, and presence of enthesitis. Conclusion Providing high data quality in large observational cohort studies is a major challenge, which requires careful monitoring. An automated monitoring process was successfully implemented and well accepted by the study centers. Two thirds of the queries were answered with new data. While conventional manual monitoring is resource-intensive and may itself create new sources of errors, automated processes are a convenient way to augment data quality.

scholarly journals Antidepressant dose and the risk of deliberate self-harm

2014 ◽  
Vol 23 (4) ◽  
pp. 329-331 ◽  
Author(s):  
C. Barbui ◽  
S.B. Patten
Keyword(s):  
Cohort Study ◽  
Clinical Practice ◽  
Propensity Score ◽  
Adverse Effects ◽  
Suicidal Behaviour ◽  
Research Question ◽  
Observational Cohort Study ◽  
Panic Attacks ◽  
Observational Cohort ◽  
Self Harm

Although the mechanism by which antidepressants (ADs) may increase the risk of suicide-related outcomes is unknown, it has been hypothesised that some adverse effects, including akathisia, insomnia and panic attacks, as well as an early energising effect that might allow patients with depression to act on suicidal impulses, may have a key role. Considering that these adverse effects are dose-related, it might be hypothesised that the risk of suicidal behaviour is similarly related to the AD dose. This research question has recently been addressed by a propensity score-matched observational cohort study that involved 162 625 patients aged 10–64 years with a depression diagnosis who initiated therapy with citalopram, sertraline or fluoxetine. In this commentary, we discuss the main findings of this study in view of its methodological strengths and limitations, and we suggest possible implications for day-to-day clinical practice.

Abstract 205: New Onset Heart Failure and Adverse Ischemic Events Associated with Amiodarone and Dronedarone Use among Atrial Fibrillation Patients

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Gosia Sylwestrzak ◽  
Jinan Liu ◽  
Alan Rosenberg ◽  
Jeffrey White ◽  
John Barron ◽  
...  
Keyword(s):  
Heart Failure ◽  
Atrial Fibrillation ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Incidence Rate ◽  
Statistical Significance ◽  
Administrative Claims ◽  
Risk Of Death ◽  
Observational Cohort ◽  
New Onset

Background: Dronedarone is a non-iodinated form of amiodarone that may not cause some of serious adverse effects associated with amiodarone. However, it is less effective than amiodarone in maintaining normal sinus rhythm, and it does not improve success of electrical cardioversion. Additionally, dronedarone use has been associated with new onset or worsening of heart failure (HF), including a doubling of the risk of death in patients with symptomatic heart failure. We aimed to compare the incidence of newly diagnosed HF and HF hospitalizations among dronedarone and amiodarone users. Secondary outcomes of interest included rates of acute ischemic stroke (IS) and transient ischemic attack (TIA). Methods: This retrospective study utilized administrative claims data between 1/1/2007-9/30/2011 from the HealthCore Integrated Research Environment (HIRE ® ). Patients were required to have at least one claim for atrial fibrillation. Propensity score matching was employed to adjust for differences between the cohorts. Incidence rate of HF, HF hospitalizations, IS and TIA events were compared between matched cohorts using Poisson time-to-event model. Results: The cohort consisted of 6,013 amiodarone and 1,534 dronedarone patients. Dronedarone patients were younger, healthier per Deyo-Charlson Index (DCI) and CHADS2 score, and less likely to have underlying heart disease (all p-values<0.05). In the propensity score matching process 838 patients with comparable baseline characteristics were selected in each group. Median follow up was 552 days in the amiodarone cohort and 412 days in the dronedarone cohort. Among patients without HF history, new onset HF incidence rate was 34.6 per 100 person-year in amiodarone cohort and 19.1 per 100 person-year in dronedarone cohort (IRR=1.61, 95% CI: 1.30-2.01, p<0.01). The incidence rate for HF hospitalization was also higher in amiodarone patients-- 10.7 per 100 person-year against 7.8 per 100 person-year for dronedarone (IRR=1.39, 95% CI: 1.02-1.85, p=0.03). For IS, the incidence rate was 1.68 per 100 person-year in amiodarone vs. 0.84 in dronedarone but results did not reach statistical significance (IRR=1.91, 95% CI: 0.84-4.30, p=0.12); for TIA, it was 3.67 vs. 2.35 for amiodarone and dronedarone respectively (IRR=2.01, 95% CI: 1.14-3.57, p=0.02). Conclusions: In a propensity score matched observational cohort study, amiodarone use was associated with higher incidence rate of new onset HF, HF hospitalizations, and TIA as identified from claims. This finding differs from other clinical studies. Future observational cohort studies should incorporate medical record review for validation since information from claims might be insufficient to fully account for underlying patient risk status, or accurately determine if HF was new onset. Key words: amiodarone; dronedarone; atrial fibrillation; heart failure.

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