Bayesian approaches to include real-world data in clinical studies

Randomized clinical trials have been the mainstay of clinical research, but are prohibitively expensive and subject to increasingly difficult patient recruitment. Recently, there is a movement to use real-world data (RWD) from electronic health records, patient registries, claims data and other sources in lieu of or supplementing controlled clinical trials. This process of combining information from diverse sources calls for inference under a Bayesian paradigm. We review some of the currently used methods and a novel non-parametric Bayesian (BNP) method. Carrying out the desired adjustment for differences in patient populations is naturally done with BNP priors that facilitate understanding of and adjustment for population heterogeneities across different data sources. We discuss the particular problem of using RWD to create a synthetic control arm to supplement single-arm treatment only studies. At the core of the proposed approach is the model-based adjustment to achieve equivalent patient populations in the current study and the (adjusted) RWD. This is implemented using common atoms mixture models. The structure of such models greatly simplifies inference. The adjustment for differences in the populations can be reduced to ratios of weights in such mixtures. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

Interrelationship between iodine nutritional status of lactating mothers and their absolutely breast-fed infants in coastal districts of Gangetic West Bengal in India

Iodine nutritional status of 128 lactating mothers and their breast-fed infants (1-3 months) from iodine-replete villages during post-salt iodization period was evaluated. Mothers' urine, blood, and breast milk (BM) and infants' urine and blood were collected and analyzed for iodine and serum FT₄ and TSH estimation. Mothers' and infants' age, parity, occupation, education, and household income were recorded. Median urinary iodine concentration (UIC) of infants was 250 μg/L, indicating their iodine intake was more than adequate. Mothers' median UIC was 185 μg/L, indicating adequate iodine nutrition; however, 13.28% had mild to severe deficiency. Median breast milk iodine concentration (BMIC) was 230 μg/L, which was more than their median UIC 185 μg/L. In iodine-deficient mothers, positive correlation was found between mothers' and infants' serum FT₄ and TSH levels, and negative correlation was found between mothers' and infants' serum FT₄ and TSH levels in excessive iodine nutrition group.

CONCLUSION

Iodine intake of breast-fed infants was at the limit of above requirement, and they are possibly at the risk of excess iodine intake. In iodine deficient and excessive iodine intake mothers, their infants' serum FT₄ and TSH are independent on their iodine nutritional status but dependent on thyroid hormone profile of their mothers but differently. What is Known: • A median urinary iodine of 100 μg/L is used to define adequate iodine intake of lactating mothers and children < 2 years. However, adequate iodine intake in terms of urinary iodine of infants of age 1-3 months is not known. What is New: • Iodine intake of absolutely breast-fed infants (1-3 months) was more than adequate, though their mother's intake was adequate as breast milk contains more iodine than urine. The infants of iodine deficient and excessive iodine intake mothers, infants' hormonal profile is independent of their iodine nutritional status but dependent on their mothers thyroid hormone profile.