Transporting survival of an HIV clinical trial to the external target populations.

Due to the heterogeneity of the randomized controlled trial (RCT) and external target populations, the estimated treatment effect from the RCT is not directly applicable to the target population. For example, the patient characteristics of the ACTG 175 HIV trial are significantly different from that of the three external target populations of interest: US early-stage HIV patients, Thailand HIV patients, and southern Ethiopia HIV patients. This paper considers several methods to transport the treatment effect from the ACTG 175 HIV trial to the target populations beyond the trial population. Most transport methods focus on continuous and binary outcomes; on the contrary, we derive and discuss several transport methods for survival outcomes: an outcome regression method based on a Cox proportional hazard (PH) model, an inverse probability weighting method based on the models for treatment assignment, sampling score, and censoring, and a doubly robust method that combines both methods, called the augmented calibration weighting (ACW) method. However, as the PH assumption was found to be incorrect for the ACTG 175 trial, the methods that depend on the PH assumption may lead to the biased quantification of the treatment effect. To account for the violation of the PH assumption, we extend the ACW method with the linear spline-based hazard regression model that does not require the PH assumption. Applying the aforementioned methods for transportability, we explore the effect of PH assumption, or the violation thereof, on transporting the survival results from the ACTG 175 trial to various external populations.

Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation.

We propose a test-based elastic integrative analysis of the randomised trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilising the trial design, we construct a test to decide whether or not to use real-world data. We characterise the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mean square error and an elastic confidence interval with a good finite-sample coverage property.

Advanced trophectoderm quality increases the risk of a large for gestational age baby in single frozen-thawed blastocyst transfer cycles.

STUDY QUESTION: Does trophectoderm (TE) quality affect birthweight after single frozen-thawed blastocyst transfer? SUMMARY ANSWER: Transfer of single blastocyst with advanced TE quality was associated with higher birthweight and increased risk of a large for gestational age (LGA) baby. WHAT IS KNOWN ALREADY: Transfer of blastocysts with advanced TE quality results in higher ongoing pregnancy rates and a lower miscarriage risk. However, data on the relationship between TE quality and birthweight are still lacking. STUDY DESIGN, SIZE, DURATION: This retrospective cohort study at a tertiary-care academic medical center included 1548 singleton babies born from single frozen-thawed blastocyst transfer from January 2011 to June 2019. PARTICIPANTS/MATERIALS, SETTING, METHODS: Babies were grouped into four groups according to embryo expansion (Stages 3, 4, 5 and 6), three groups according to inner cell mass (ICM) quality (A, B and C), and three groups according to TE quality (A, B and C). Main outcomes included absolute birthweight, Z-scores adjusted for gestational age and gender, and adverse neonatal outcomes. Multivariable linear and logistic regression analyses were performed to investigate the association of neonatal outcomes with expansion stage, ICM quality and TE quality. MAIN RESULTS AND THE ROLE OF CHANCE: As TE quality decreased, birthweight (3468.10 ± 471.52, 3357.69 ± 522.06, and 3288.79 ± 501.90 for A, B and C, respectively, P = 0.002), Z-scores (0.59 ± 1.07, 0.42 ± 1.04, and 0.27 ± 1.06 for A, B and C, respectively, P = 0.002) and incidence of LGA (28.9%, 19.7% and 17.4% for A, B and C, respectively, P = 0.027) decreased correspondingly. After adjusting for confounders, compared with the Grade A group, blastocysts with TE Grade B (standardized coefficients (ß): -127.97 g, 95% CI: -234.46 to -21.47, P = 0.019) and blastocysts with TE grade C (ß: -200.27 g, 95% CI: -320.69 to -79.86, P = 0.001) resulted in offspring with lower birthweight. Blastocysts with TE grade C brought babies with lower Z-scores than TE Grade A (ß: -0.35, 95% CI: -0.59 to -0.10, P = 0.005). Also, embryos with TE Grade B (adjusted odds ratio (aOR):0.91, 95% CI: 0.84 to 0.99, P = 0.033) and embryos with TE Grade C (aOR : 0.89, 95% CI: 0.81 to 0.98, P = 0.016) had lower chance of leading to a LGA baby than those with TE Grade A. No association between neonatal outcomes with embryo expansion stage and ICM was observed (all P > 0.05). LIMITATIONS, REASONS FOR CAUTION: The retrospective design, lack of controlling for several unknown confounders, and inter-observer variation limited this study. WIDER IMPLICATIONS OF THE FINDINGS: The study extends our knowledge of the down-stream effect of TE quality on newborn birthweight and the risk of LGA. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by National Key R&D Program of China (2018YFC1003000), National Natural Science Foundation of China (81771533 to Y.P.K. and 31200825 to L.S.) and Innovative Research Team of High-level Local Universities in Shanghai (SSMU-ZLCX20180401), Shanghai Sailing Program(21YF1423200) and the Fundamental research program funding of Ninth People's Hospital affiliated to Shanghai Jiao Tong university School of Medicine (JYZZ117). The authors declare no conflict of interest in this present study. TRIAL REGISTRATION NUMBER: N/A.

Nearest neighbor ratio imputation with incomplete multinomial outcome in survey sampling.

Nonresponse is a common problem in survey sampling. Appropriate treatment can be challenging, especially when dealing with detailed breakdowns of totals. Often, the nearest neighbor imputation method is used to handle such incomplete multinomial data. In this article, we investigate the nearest neighbor ratio imputation estimator, in which auxiliary variables are used to identify the closest donor and the vector of proportions from the donor is applied to the total of the recipient to implement ratio imputation. To estimate the asymptotic variance, we first treat the nearest neighbor ratio imputation as a special case of predictive matching imputation and apply the linearization method of Yang and Kim (2020). To account for the non-negligible sampling fractions, parametric and generalized additive models are employed to incorporate the smoothness of the imputation estimator, which results in a valid variance estimator. We apply the proposed method to estimate expenditures detail items based on empirical data from the 2018 collection of the Service Annual Survey, conducted by the United States Census Bureau. Our simulation results demonstrate the validity of our proposed estimators and also confirm that the derived variance estimators have good performance even when the sampling fraction is non-negligible.