Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^

A systematic review of literature to compare the fertility desires among HIV positive women and cancer survivors

Background. Decision-making on reproductive issues is influenced by an interplay of individual, familial, medical, religious and socio-cultural factors. Women with chronic medical illnesses such an HIV infection and cancers are often fraught with decisional conflicts about child-bearing. With increase in the incidence of these illnesses as well as improvement in survival rates, there is a need to pay due attention to the issue of reproductive decision-making. Examining the prevalence and determinants of fertility desires in the two groups in a comparative manner would help bring to light perception of the medical community and the society in general on the two illnesses and the issue of motherhood. ^ Methods. Systematic literature search was undertaken using databases such as MEDLINE (PubMED), MEDLINE (Ovid), PsycInfo and Web of Science. Articles published in English and English language abstracts for foreign articles were included. Studies that explore ‘fertility desires’ as the outcome variable were included. Quantitative studies which have assessed the prevalence of fertility desires as well as qualitative studies which have provided a descriptive understanding of factors governing reproductive desires were included in the review. ^ Results. A total of 34 articles (29 studies examining HIV and 5 studies examining cancer in relation to fertility desires). Variables such as age, stage of illness, support of spouse and family, perception of the medical community and one’s own view of motherhood were key determinants among both groups. ^ Conclusion. There is a need for uniform, systematic research in this field. It is important that health care workers acknowledge these decisional conflicts, include them as part of the medical care of these patients and provide guidance with the right balance of information, practicality and compassion.^