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Comparing methods for estimating patient-specific treatment effects in individual patient data meta-analysis.

ABSTRACT: Meta-analysis of individual patient data (IPD) is increasingly used to synthesize data from multiple trials. IPD meta-analysis offers several advantages over meta-analyzing aggregate data, including the capacity to individualize treatment recommendations. Trials usually collect information on many patient characteristics. Some of these covariates may strongly interact with treatment (and thus be associated with treatment effect modification) while others may have little effect. It is currently unclear whether a systematic approach to the selection of treatment-covariate interactions in an IPD meta-analysis can lead to better estimates of patient-specific treatment effects. We aimed to answer this question by comparing in simulations the standard approach to IPD meta-analysis (no variable selection, all treatment-covariate interactions included in the model) with six alternative methods: stepwise regression, and five regression methods that perform shrinkage on treatment-covariate interactions, that is, least absolute shrinkage and selection operator (LASSO), ridge, adaptive LASSO, Bayesian LASSO, and stochastic search variable selection. Exploring a range of scenarios, we found that shrinkage methods performed well for both continuous and dichotomous outcomes, for a variety of settings. In most scenarios, these methods gave lower mean squared error of the patient-specific treatment effect as compared with the standard approach and stepwise regression. We illustrate the application of these methods in two datasets from cardiology and psychiatry. We recommend that future IPD meta-analysis that aim to estimate patient-specific treatment effects using multiple effect modifiers should use shrinkage methods, whereas stepwise regression should be avoided.

SUBMITTER: Seo M

PROVIDER: S-EPMC7898845 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Comparing methods for estimating patient-specific treatment effects in individual patient data meta-analysis.

Seo Michael M White Ian R IR Furukawa Toshi A TA Imai Hissei H Valgimigli Marco M Egger Matthias M Zwahlen Marcel M Efthimiou Orestis O

Statistics in medicine 20201227 6

Meta-analysis of individual patient data (IPD) is increasingly used to synthesize data from multiple trials. IPD meta-analysis offers several advantages over meta-analyzing aggregate data, including the capacity to individualize treatment recommendations. Trials usually collect information on many patient characteristics. Some of these covariates may strongly interact with treatment (and thus be associated with treatment effect modification) while others may have little effect. It is currently u ...[more]

PMID: 33368415

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Project description:ImportanceCurrent evidence remains ambiguous regarding whether biologics should be added to conventional treatment of rheumatoid arthritis for specific patients, which may cause potential overuse or treatment delay.ObjectivesTo estimate the benefit of adding biologics to conventional antirheumatic drugs for the treatment of rheumatoid arthritis given baseline characteristics.Data sourcesCochrane CENTRAL, Scopus, MEDLINE, and the World Health Organization International Clinical Trials Registry Platform were searched for articles published from database inception to March 2, 2022.Study selectionRandomized clinical trials comparing certolizumab plus conventional antirheumatic drugs with placebo plus conventional drugs were selected.Data extraction and synthesisIndividual participant data of the prespecified outcomes and covariates were acquired from the Vivli database. A 2-stage model was fitted to estimate patient-specific relative outcomes of adding certolizumab vs conventional drugs only. Stage 1 was a penalized logistic regression model to estimate the baseline expected probability of the outcome regardless of treatment using baseline characteristics. Stage 2 was a bayesian individual participant data meta-regression model to estimate the relative outcomes for a particular baseline expected probability. Patient-specific results were displayed interactively on an application based on a 2-stage model.Main outcomes and measuresThe primary outcome was low disease activity or remission at 3 months, defined by 3 disease activity indexes (ie, Disease Activity Score based on the evaluation of 28 joints, Clinical Disease Activity Index, or Simplified Disease Activity Index).ResultsIndividual participant data were obtained from 3790 patients (2996 female [79.1%] and 794 male [20.9%]; mean [SD] age, 52.7 [12.3] years) from 5 large randomized clinical trials for moderate to high activity rheumatoid arthritis with usable data for 22 prespecified baseline covariates. Overall, adding certolizumab was associated with a higher probability of reaching low disease activity. The odds ratio for patients with an average baseline expected probability of the outcome was 6.31 (95% credible interval, 2.22-15.25). However, the benefits differed in patients with different baseline characteristics. For example, the estimated risk difference was smaller than 10% for patients with either low or high baseline expected probability.Conclusions and relevanceIn this individual participant data meta-analysis, adding certolizumab was associated with more effectiveness for rheumatoid arthritis in general. However, the benefit was uncertain for patients with low or high baseline expected probability, for whom other evaluations were necessary. The interactive application displaying individual estimates may help with treatment selection.

Project description:BackgroundThe 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements.MethodsAccess to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) - the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity.ResultsIPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant.ConclusionsOverall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

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Project description:PURPOSE:To evaluate short- and long-term technical and clinical outcomes after kissing stent treatment of aortoiliac occlusive disease (AIOD) based on an individual participant data (IPD) meta-analysis. MATERIALS AND METHODS:A search of the Scopus database identified 156 articles on KS treatment of AIOD; of these 22 met the inclusion criteria. Authors of 19 articles with contact information were approached to join an IPD consortium. Eight author groups responded and 5 provided anonymized data for merging into an IPD database. The number of included procedures was equal before and after 2005. The primary study outcome was the cumulative patency at 24 months. Secondary outcomes were patency at up to 60 months, complications, and changes in Rutherford category and ankle-brachial index. The predictive value of stent protrusion length, pre-/postdilation, stent type, and patient demographics on primary patency were examined with Cox proportional hazard modeling; outcomes are reported as the hazard ratio (HR). The Kaplan-Meier method was employed to estimate patency rates. RESULTS:In total, 605 (40.9%) of 1480 patients presented in the literature were included in the IPD analysis. The indication for intervention was intermittent claudication in 84.2% and critical limb ischemia in 15.8%. Lesions were classified as TransAtlantic Inter-Society Consensus (TASC) A or B in 52.8% and TASC C and D in 47.2%. The overall primary patency estimate was 81% at 24 months. Primary patency significantly increased after 2005 (p=0.005). Cox regression analysis revealed only age as a significant predictor of sustained primary patency (HR 0.60, p<0.005). Any previous endovascular intervention (HR 2.52, p=0.02) was the main predictor for loss of secondary patency; history of cardiovascular disease (HR 0.27, p=0.04) was the main predictor of sustained secondary patency. CONCLUSION:The kissing stent technique has a good safety profile and acceptable patency rates up to 2 years, even in TASC C and D lesions, supporting an endovascular-first approach for AIOD.

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Comparing methods for estimating patient-specific treatment effects in individual patient data meta-analysis.

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Comparing methods for estimating patient-specific treatment effects in individual patient data meta-analysis.

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