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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 naïve 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.

ObjectiveFew prospective studies have assessed whether individuals with subclinical thyroid dysfunction are more likely to develop diabetes, with conflicting results. In this study, we conducted a systematic review of the literature and an individual participant data analysis of multiple prospective cohorts to investigate the association between subclinical thyroid dysfunction and incident diabetes.MethodsWe performed a systematic review of the literature in Medline, Embase, and the Cochrane Library from inception to February 11, 2022. A two-stage individual participant data analysis was conducted to compare participants with subclinical hypothyroidism and subclinical hyperthyroidism vs euthyroidism at baseline and the adjusted risk of developing diabetes at follow-up.ResultsAmong 61 178 adults from 18 studies, 49% were females, mean age was 58 years, and mean follow-up time was 8.2 years. At the last available follow-up, there was no association between subclinical hypothyroidism and incidence of diabetes (odds ratio (OR) = 1.02, 95% CI: 0.88–1.17, I2 = 0%) or subclinical hyperthyroidism and incidence of diabetes (OR = 1.03, 95% CI: 0.82–1.30, I2 = 0%), in age- and sex-adjusted analyses. Time-to-event analysis showed similar results (hazard ratio for subclinical hypothyroidism: 0.98, 95% CI: 0.87–1.11; hazard ratio for subclinical hyperthyroidism: 1.07, 95% CI: 0.88–1.29). The results were robust in all sub-group and sensitivity analyses.ConclusionsThis is the largest systematic review and individual participant data analysis to date investigating the prospective association between subclinical thyroid dysfunction and diabetes. We did not find an association between subclinical thyroid dysfunction and incident diabetes. Our results do not support screening patients with subclinical thyroid dysfunction for diabetes.Significance statementEvidence is conflicting regarding whether an association exists between subclinical thyroid dysfunction and incident diabetes. We therefore aimed to investigate whether individuals with subclinical thyroid dysfunction are more prone to develop diabetes in the long run as compared to euthyroid individuals. We included data from 18 international cohort studies with 61 178 adults and a mean follow-up time of 8.2 years. We did not find an association between subclinical hypothyroidism or subclinical hyperthyroidism at baseline and incident diabetes at follow-up. Our results have clinical implications as they neither support screening patients with subclinical thyroid dysfunction for diabetes nor treating them in the hope of preventing diabetes in the future. Objective: Few prospective studies have assessed whether individuals with subclinical thyroid dysfunction are more likely to develop diabetes, with conflicting results. In this study, we conducted a systematic review of the literature and an individual participant data analysis of multiple prospective cohorts to investigate the association between subclinical thyroid dysfunction and incident diabetes. Methods: We performed a systematic review of the literature in Medline, Embase, and the Cochrane Library from inception to February 11, 2022. A two-stage individual participant data analysis was conducted to compare participants with subclinical hypothyroidism and subclinical hyperthyroidism vs euthyroidism at baseline and the adjusted risk of developing diabetes at follow-up. Results: Among 61 178 adults from 18 studies, 49% were females, mean age was 58 years, and mean follow-up time was 8.2 years. At the last available follow-up, there was no association between subclinical hypothyroidism and incidence of diabetes (odds ratio (OR) = 1.02, 95% CI: 0.88-1.17, I2 = 0%) or subclinical hyperthyroidism and incidence of diabetes (OR = 1.03, 95% CI: 0.82-1.30, I2 = 0%), in age- and sex-adjusted analyses. Time-to-event analysis showed similar results (hazard ratio for subclinical hypothyroidism: 0.98, 95% CI: 0.87-1.11; hazard ratio for subclinical hyperthyroidism: 1.07, 95% CI: 0.88-1.29). The results were robust in all sub-group and sensitivity analyses. Conclusions: This is the largest systematic review and individual participant data analysis to date investigating the prospective association between subclinical thyroid dysfunction and diabetes. We did not find an association between subclinical thyroid dysfunction and incident diabetes. Our results do not support screening patients with subclinical thyroid dysfunction for diabetes. Significance statement: Evidence is conflicting regarding whether an association exists between subclinical thyroid dysfunction and incident diabetes. We therefore aimed to investigate whether individuals with subclinical thyroid dysfunction are more prone to develop diabetes in the long run as compared to euthyroid individuals. We included data from 18 international cohort studies with 61 178 adults and a mean follow-up time of 8.2 years. We did not find an association between subclinical hypothyroidism or subclinical hyperthyroidism at baseline and incident diabetes at follow-up. Our results have clinical implications as they neither support screening patients with subclinical thyroid dysfunction for diabetes nor treating them in the hope of preventing diabetes in the future.

Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism., Author Summary Levels of thyroid hormones are tightly regulated by TSH produced in the pituitary, and even mild alterations in their concentrations are strong indicators of thyroid pathologies, which are very common worldwide. To identify common genetic variants associated with the highly heritable markers of thyroid function, TSH and FT4, we conducted a meta-analysis of genome-wide association studies in 26,420 and 17,520 individuals, respectively, of European ancestry with normal thyroid function. Our analysis identified 26 independent genetic variants regulating these traits, several of which are new, and confirmed previously detected polymorphisms affecting TSH (within the PDE8B gene and near CAPZB, MAF/LOC440389, and NR3C2) and FT4 (within DIO1) levels. Gender-specific differences in the genetic effects of several variants for TSH and FT4 levels were identified at several loci, which offer clues to understand the known sexual dimorphism in thyroid function and pathology. Of particular clinical interest, we show that TSH-associated loci contribute not only to normal variation, but also to TSH values outside reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings add to the developing landscape of the regulation of thyroid homeostasis and the consequences of genetic variation for thyroid related diseases.