Body mass index and patient-reported function, quality of life and treatment toxicity in women receiving adjuvant chemotherapy for breast cancer.

BACKGROUND: This study investigates whether high body mass index (BMI) in women diagnosed with early breast cancer (BC) is associated with patient-reported symptom severity during chemotherapy. METHODS: Women with Stage I-III BC completed toxicity reports for 17 side effects throughout regularly scheduled chemotherapy infusions. Toxicity reports were compared in women with obesity (BMI > = 30) versus no obesity (BMI < 30). Fisher's exact tests and 2-sample t-tests compared baseline patient characteristics. Risk ratios (RR) for women with obesity as compared to no obesity were estimated for individual symptoms that were patient-rated as moderate, severe or very severe (MSVS) severity, adjusting for marital status and race. RESULTS: In a sample of 286 patients, Black women comprised 23% of the sample. The obesity rate was 76% among Black patients and 31% among White patients (p < .0001). Women with obesity rated an average of 6.9 side effects (standard deviation, SD 4.2) as MSVS vs 5.5 side effects (SD 3.7) among women with no obesity (p = .003). In adjusted analysis, women with obesity had significantly greater risk for MSVS fatigue (RR 1.18, 95% CI 1.01-1.36), dyspnea (RR 1.71, 95% CI 1.09-2.69), arthralgia (RR 1.47, 95% CI 1.10-1.97), peripheral neuropathy (RR 1.45, 95% CI 1.01-2.08), edema of limbs (RR 1.84, 95% CI 1.18-2.88), and abdominal pain (RR 1.75, 95% CI 1.07-2.87). There were no inter-group differences in BC stage or phenotype, chemotherapy treatment modifications, or hospitalizations. CONCLUSIONS: Among women with early BC, patients with obesity reported higher chemotherapy toxicity as compared to patients without obesity; however, this did not result in differences in treatment completion.

Futility stopping in clinical trials, optimality and practical considerations.

Stopping for futility is a useful tool in a clinical trial. It is widely used in single-arm trials in oncology and in many two-arm trials. We review three stopping rules for futility. We give recommendations for the optimal timing of futility looks in two-stage trials in terms of the information fraction and the probability of stopping under the alternative hypothesis. We discuss futility stopping in trials with substantial uncertainty about the variability of the outcome and in crossover trials.

Translational studies of phenotypic probes for the mononuclear phagocyte system and liposomal pharmacology.

As nanoparticles (NPs) are cleared via phagocytes of the mononuclear phagocyte system (MPS), we hypothesized that the function of circulating monocytes and dendritic cells (MO/DC) in blood can predict NP clearance (CL). We measured MO/DC phagocytosis and reactive oxygen species (ROS) production in mice, rats, dogs, and patients with refractory solid tumors. Pharmacokinetic studies of polyethylene glycol (PEG)-encapsulated liposomal doxorubicin (PEGylated liposomal doxirubicin [PLD]), CKD-602 (S-CKD602), and cisplatin (SPI-077) were performed at the maximum tolerated dose. MO/DC function was also evaluated in patients with recurrent epithelial ovarian cancer (EOC) administered PLD. Across species, a positive association was observed between cell function and CL of PEGylated liposomes. In patients with EOC, associations were observed between PLD CL and phagocytosis (R(2) = 0.43, P = 0.04) and ROS production (R(2) = 0.61, P = 0.008) in blood MO/DC. These findings suggest that probes of MPS function may help predict PEGylated liposome CL across species and PLD CL in patients with EOC.

Kappa statistic for clustered dichotomous responses from physicians and patients.

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared with the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. We present an example of an application to a coronary heart disease prevention study.

Revisiting the X:BOT Naltrexone Clinical Trial Using a Comprehensive Survival Analysis.

OBJECTIVES: This paper illustrates survival models for analysis of trials of substance use treatment programs. It uses public release data from a study of extended-release naltrexone (XR-NTX), relative to buprenorphine-naloxone (BUP-NX). METHODS: We used publicly available data from the X:BOT trial (n = 570), which compared XR-NTX to BUP-NX on 2 efficacy outcomes (opioid relapse, use of nonprescribed opioids; positive opioid urine test) and 1 safety outcome (overdose). Intention-to-treat (ITT) and per-protocol approaches were implemented using survival models that included treatment-by-time interactions. RESULTS: Consistent with the original trial findings, 72% of XR-NTX and 94% of BUP-NX subjects initiated treatment; the ITT hazard ratio for XR-NTX relative to BUP-NX was 1.40 (95% confidence interval: 1.13, 1.73; P < 0.01) for opioid relapse and 1.31 (1.07, 1.60; P = 0.01) for positive urine test. Using treatment-by-time interactions, we examined the time-dependent effect of XR-NTX and found an elevated ITT overdose hazard ratio of 2.4 (1.1, 5.3; P = 0.03) overall and 3.8 (1.2, 11.6; P = 0.02) during the study treatment phase. This result (28 overdoses overall; 17 overdoses during the study treatment phase) contrasts with the previous analysis, which reported minimal differences in overdose between XR-NTX and BUP-NX. CONCLUSIONS: An advantage of using time-dependent Cox models is its ability to isolate effects during specific periods. In general, our survival analyses concur with the conclusions of Lee et al (2018) for the efficacy outcomes, which demonstrated superiority of BUP-NX. In contrast to the original report, our analysis indicates a greater risk of overdose for XR-NTX, predominantly during the study treatment phase. Further investigation of this finding is a pressing research priority.

Tobacco smoke exposure and altered nasal responses to live attenuated influenza virus.

BACKGROUND: Epidemiologic evidence links tobacco smoke and increased risk for influenza in humans, but the specific host defense pathways involved are unclear. OBJECTIVE: We developed a model to examine influenza-induced innate immune responses in humans and test the hypothesis that exposure to cigarette smoke alters nasal inflammatory and antiviral responses to live attenuated influenza virus (LAIV). METHODS: This was an observational cohort study comparing nasal mucosal responses to LAIV among young adult active smokers (n = 17), nonsmokers exposed to secondhand smoke (SHS; n = 20), and unexposed controls (n = 23). Virus RNA and inflammatory factors were measured in nasal lavage fluids (NLF) serially after LAIV inoculation. For key end points, peak and total (area under curve) responses were compared among groups. RESULTS: Compared with controls, NLF interleukin-6 (IL-6) responses to LAIV (peak and total) were suppressed in smokers. Virus RNA in NLF cells was significantly increased in smokers, as were interferon-inducible protein 10:virus ratios. Responses in SHS-exposed subjects were generally intermediate between controls and smokers. We observed significant associations between urine cotinine and NLF IL-6 responses (negative correlation) or virus RNA in NLF cells (positive correlation) for all subjects combined. CONCLUSIONS: Nasal inoculation with LAIV results in measurable inflammatory and antiviral responses in human volunteers, thus providing a model for investigating environmental effects on influenza infections in humans. Exposure to cigarette smoke was associated with suppression of specific nasal inflammatory and antiviral responses, as well as increased virus quantity, after nasal inoculation with LAIV. These data suggest mechanisms for increased susceptibility to influenza infection among persons exposed to tobacco smoke.

Bootstrap analysis of multivariate failure time data.

Multivariate failure time data often arise in research. Cox proportional hazards modelling is a widely used method of analysing failure time data for independent observations. However, when failure times are correlated the Cox proportional hazards model does not yield valid estimates of standard errors or significance tests. Many methods for the analysis of multivariate failure time data have been proposed. These methods commonly test hypotheses about the regression parameters, a practice which averages the treatment effect across time. The purpose of this paper is to examine the bootstrap method for obtaining standard errors in the multivariate failure time case, particularly when the focus is the survival probability or the treatment effect at a single time point such as in a surgical trial. Our motivating example comes from the Asymptomatic Carotid and Atherosclerosis Study (ACAS) in which the outcome of stroke or perioperative complications could be observed for either or both carotid arteries within each patient. Extensive simulation studies were conducted to examine the bootstrap procedure for analysing correlated failure time data under a variety of conditions including a range of treatment effects, cluster sizes, intercluster correlation values and for both proportional and non-proportional data. We found that the bootstrap method was able to estimate the standard error adequately for survival probabilities at a specific time and the standard error for the survival difference and the relative risk at a specific time. We illustrated the bootstrap method for calculating the standard error for the survival probability and statistical testing at a specific time value by analysing the two arteries per patient from the ACAS study.