Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies

BackgroundIn non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC). MethodsFor the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naive approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA. ResultsTen of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score. ConclusionANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly

Thyroid function tests in the reference range and fracture: Individual participant analysis of prospective cohorts

Context: Hyperthyroidism is associated with increased fracture risk, but it is not clear if lower thyroid-stimulating hormone (TSH) and higher free thyroxine (FT4) in euthyroid individuals are associated with fracture risk. Objective: To evaluate the association of TSH and FT4 with incident fractures in euthyroid individuals. Design: Individual participant data analysis. Setting: Thirteen prospective cohort studies with baseline examinations between 1981 and 2002. Participants: Adults with baseline TSH 0.45 to 4.49 mIU/L. Main Outcome Measures: Primary outcome was incident hip fracture. Secondary outcomes were any, nonvertebral, and vertebral fractures. Results were presented as hazard ratios (HRs) with 95% confidence interval (CI) adjusted for age and sex. For clinical relevance, we studied TSH according to five categories: 0.45 to 0.99 mIU/L; 1.00 to 1.49 mIU/L; 1.50 to 2.49 mIU/L; 2.50 to 3.49 mIU/L; and 3.50 to 4.49 mIU/L (reference). FT4 was assessed as study-specific standard deviation increase, because assays varied between cohorts. Results: During 659,059 person-years, 2,565 out of 56,835 participants had hip fracture (4.5%; 12 studies with data on hip fracture). The pooled adjusted HR (95% CI) for hip fracture was 1.25 (1.05 to 1.49) for TSH 0.45 to 0.99 mIU/L, 1.19 (1.01 to 1.41) for TSH 1.00 to 1.49 mIU/L, 1.09 (0.93 to 1.28) for TSH 1.50 to 2.49 mIU/L, and 1.12 (0.94 to 1.33) for TSH 2.50 to 3.49 mIU/L (P for trend = 0.004). Hip fracture was also associated with FT4 [HR (95% CI) 1.22 (1.11 to 1.35) per one standard deviation increase in FT4]. FT4 only was associated with any and nonvertebral fractures. Results remained similar in sensitivity analyses. Conclusions: Among euthyroid adults, lower TSH and higher FT4 are associated with an increased risk of hip fracture. These findings may help refine the definition of optimal ranges of thyroid function tests