FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1566271801> ?p ?o ?g. }

• W1566271801 abstract "Inferences about intended effects of treatments are ideally investigated using randomized control trials (RCTs). Randomization leads to comparability of treated and comparison groups on measured and unmeasured prognostic factors, except the treatment, thereby preventing confounding. RCTs, however, may not always be feasible or necessary, for example, in drug-safety research involving unpredictable adverse events. However, when adverse events are related to the main effects of the therapy, patient’s prognosis and the potential for adverse events guide prescribing behavior leading to systematic differences in prognostic factors between treated groups. Hence, confounding by (contra-)indication is a threat to internal validity of the study results. Therefore, inferences from non-randomized studies require that the studies be designed like RCTs (e.g., using propensity score (PS) matching or weighting, i.e., design and analysis are apart) or confounders are accounted for (PS stratification or covariance adjustment, i.e., analysis stage) or a combination of the two (PS matching/weighting combined with covariate adjustment). The PS is the probability of receiving a particular treatment conditional on measured covariates, i.e., patient’s treatment in daily practice is predicted using prognostic factors. PS methods can be considered the observational study analogues of randomization in RCTs although PS methods attempt to balance only measured factors. Under the assumption of no unmeasured confounding given the PS, PS methods help researchers design and analyze observational studies in a way that mimics RCTs. We studied different aspects of the PS methods in pharmacoepidemiology. First, we focused on covariate selection, assessment as well as reporting of covariate balance using different balance metrics in PS analysis. We provided a checklist for reporting PS analysis and recommended the standardized difference for measuring and reporting covariate balance, PS model selection, and choosing optimal caliper width in PS matching. Next, we demonstrated marginal structural models, whose parameters are estimated using inverse probability of treatment weights, when treatment is time-varying and confounding is time-dependent using clinical examples. Results were compared with those of conventional time-varying Cox regression and PS methods. Further, the assumptions underlying PS methods, particularly of unmeasured confounding, and advantages of PS methods, compared to regression approaches in pharmacoepidemiology were discussed. Moreover, We extended the use of balance measures for quantitative falsification of instrumental variables assumptions thereby helping researchers’ decision on whether to proceed with or refrain from instrumental variable analysis. Finally, we provided a guidance document comprising a step-by-step description of the PS methodology and interpretations of effect estimates from different PS approaches. In conclusion, we argue that PS methods are invaluable tools for estimating treatment effects using observational data; their use is optimal when combined with model-based adjustment. In addition to initial designing of the study, full specification of all analyses performed is required for utilizing full advantage of the PS methods. Furthermore, adequate reporting of aspects of the PS analysis is as crucial as the analysis itself, since readers rely on this information for better appraisal of the quality of the study and validity of the results. Hence, critical items of PS analysis should be incorporated in guidelines on the conduct and reporting of observational studies, such as the STROBE statement and the ENCePP guide on methodological standards in pharmacoepidemiology to improve the quality of conduct and reporting PS based studies." @default.
• W1566271801 created "2016-06-24" @default.
• W1566271801 creator A5011949935 @default.
• W1566271801 date "2014-10-01" @default.
• W1566271801 modified "2023-09-27" @default.
• W1566271801 title "Improving Propensity Score Methods in Pharmacoepidemiology" @default.
• W1566271801 cites W1501511408 @default.
• W1566271801 cites W1506399260 @default.
• W1566271801 cites W1507159634 @default.
• W1566271801 cites W1508060799 @default.
• W1566271801 cites W1521836421 @default.
• W1566271801 cites W1524822070 @default.
• W1566271801 cites W1553139968 @default.
• W1566271801 cites W1557758852 @default.
• W1566271801 cites W1580788756 @default.
• W1566271801 cites W1601608895 @default.
• W1566271801 cites W1752500127 @default.
• W1566271801 cites W182119280 @default.
• W1566271801 cites W1830611402 @default.
• W1566271801 cites W1915430721 @default.
• W1566271801 cites W1928755576 @default.
• W1566271801 cites W1964475341 @default.
• W1566271801 cites W1967862917 @default.
• W1566271801 cites W1969479683 @default.
• W1566271801 cites W1969503074 @default.
• W1566271801 cites W1973285887 @default.
• W1566271801 cites W1973683188 @default.
• W1566271801 cites W1973948212 @default.
• W1566271801 cites W1978108654 @default.
• W1566271801 cites W1978209044 @default.
• W1566271801 cites W1978697775 @default.
• W1566271801 cites W1979202959 @default.
• W1566271801 cites W1980412904 @default.
• W1566271801 cites W1982146393 @default.
• W1566271801 cites W1982910299 @default.
• W1566271801 cites W1984250866 @default.
• W1566271801 cites W1984262040 @default.
• W1566271801 cites W1984454461 @default.
• W1566271801 cites W1988339318 @default.
• W1566271801 cites W1989377468 @default.
• W1566271801 cites W1989804742 @default.
• W1566271801 cites W1992882281 @default.
• W1566271801 cites W1993980658 @default.
• W1566271801 cites W1996016456 @default.
• W1566271801 cites W1996351770 @default.
• W1566271801 cites W1999822211 @default.
• W1566271801 cites W2000991311 @default.
• W1566271801 cites W2001947543 @default.
• W1566271801 cites W2002471042 @default.
• W1566271801 cites W2002595054 @default.
• W1566271801 cites W2002646960 @default.
• W1566271801 cites W2006623746 @default.
• W1566271801 cites W2008557562 @default.
• W1566271801 cites W2008662928 @default.
• W1566271801 cites W2008706768 @default.
• W1566271801 cites W2009187570 @default.
• W1566271801 cites W2009688407 @default.
• W1566271801 cites W2011795361 @default.
• W1566271801 cites W2013112027 @default.
• W1566271801 cites W2014530124 @default.
• W1566271801 cites W2015501013 @default.
• W1566271801 cites W2016403661 @default.
• W1566271801 cites W2018270810 @default.
• W1566271801 cites W2022211849 @default.
• W1566271801 cites W2022439966 @default.
• W1566271801 cites W2024861369 @default.
• W1566271801 cites W2028040032 @default.
• W1566271801 cites W2030614017 @default.
• W1566271801 cites W2034309896 @default.
• W1566271801 cites W2034806082 @default.
• W1566271801 cites W2035305268 @default.
• W1566271801 cites W2035481234 @default.
• W1566271801 cites W2036193982 @default.
• W1566271801 cites W2037135054 @default.
• W1566271801 cites W2037668591 @default.
• W1566271801 cites W2037850256 @default.
• W1566271801 cites W2041303993 @default.
• W1566271801 cites W2044155913 @default.
• W1566271801 cites W2044325065 @default.
• W1566271801 cites W2045949527 @default.
• W1566271801 cites W2047993093 @default.
• W1566271801 cites W2048565444 @default.
• W1566271801 cites W2049910836 @default.
• W1566271801 cites W2050986127 @default.
• W1566271801 cites W2051375321 @default.
• W1566271801 cites W2051866975 @default.
• W1566271801 cites W2052806549 @default.
• W1566271801 cites W2055296410 @default.
• W1566271801 cites W2060316606 @default.
• W1566271801 cites W2060350588 @default.
• W1566271801 cites W2061407842 @default.
• W1566271801 cites W2062417462 @default.
• W1566271801 cites W2062594082 @default.
• W1566271801 cites W2063227395 @default.
• W1566271801 cites W2063548620 @default.
• W1566271801 cites W2065126224 @default.
• W1566271801 cites W2065616395 @default.
• W1566271801 cites W2073225472 @default.
• W1566271801 cites W2076035149 @default.
• W1566271801 cites W2076731491 @default.

• next