Design considerations and analytical framework for reliably identifying a beneficial individualized treatment rule.

An individualized treatment rule (ITR) formalizes personalized medicine by assigning treatment as a function of patients' clinical information, which contrasts with a static treatment rule that assigns everyone the same treatment. ITR identification has become a common aim in randomized clinical trials but sample size considerations for this aim are lacking. One approach is to select a sample size that will reliably identify an ITR with a performance close to the theoretical optimal rule. However, this approach could still lead to identifying ITRs that perform worse than the optimal static rule, particularly in the absence of substantial effect heterogeneity. This limitation motivates sample size considerations aimed at reliable identification of a beneficial ITR, which outperforms the optimal static rule, and analysis methods that identify the estimated optimal static rule when there is substantial uncertainty about whether an ITR will improve outcomes. To address these limitations, we propose a sample size approach based on the probability of identifying a beneficial ITR and introduce an approach for selecting the LASSO penalty parameter such that in the absence of treatment effect heterogeneity the estimated optimal static rule is identified with high probability. We apply these approaches to the PLUTO trial aimed at developing methods to assist with smoking cessation.

Urination Frequency Ranges in Healthy Women.

BACKGROUND: Limited information on the normal range of urination frequencies in women is available to guide bladder health promotion efforts. OBJECTIVES: This study used data from the Boston Area Community Health (BACH) Survey to (a) estimate normative reference ranges in daytime and nighttime urination frequencies in healthy women based on two operational definitions of "healthy" and (b) compare urination frequencies by age, race/ethnicity, and fluid intake. METHODS: A secondary analysis of cross-sectional interview data collected from female participants was performed using less restrictive ("healthy") and strict ("elite healthy") inclusion criteria. All analyses were weighted to account for the BACH sampling design. Normative reference values corresponding to the middle 95% of the distribution of daytime and nighttime urination frequencies were calculated overall and stratified by age, race/ethnicity, and fluid intake. Generalized linear regression with a log-link was used to estimate rate ratios of daytime and nighttime urination frequencies by age, race/ethnicity, and fluid intake. RESULTS: Of the 2,534 women who completed the BACH follow-up interviews, 1,505 women met healthy eligibility criteria, and 300 met elite healthy criteria. Overall, reference ranges for urination frequencies were 2-10 times/day and 0-4 times/night in healthy women and 2-9 times/day and 0-2 times/night in elite healthy women. Women ages 45-64 years, but not 65+ years, reported a greater number of daytime urination than those aged 31-44 years, whereas women 65+ years reported a greater number of nighttime urination. Black women reported fewer daytime urination and more nighttime urinations than White women. Women who consumed less than 49 oz daily reported fewer daytime and nighttime urinations than those who drank 50-74 oz; drinking 75+ oz had only a small effect on urination frequencies. DISCUSSION: Normative reference values for daytime and nighttime urination frequencies were similar in women using strict and relaxed definitions of health. These results indicate a wide range of "normal" urination frequencies, with some differences by age, race/ethnicity, and fluid intake. Future research is needed to examine urination frequencies in minority women and whether fluid intake amount and type influence the development of lower urinary tract symptoms.