We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse event data. Special attention is paid to the case of rare adverse events which are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We derive three new methods, simple (unweighted) average treatment effect estimator, a new heterogeneity estimator, and a parametric bootstrapping test for heterogeneity. We then study the statistical properties of both the traditional and new methods via simulation. We find that in general, moment-based estimators of combined treatment effects and heterogeneity are biased and the degree of bias is proportional to the rarity of the event under study. The new methods eliminate much, but not all of this bias. The various estimators and hypothesis testing methods are then compared and contrasted using an example dataset on treatment of stable coronary artery disease.
Objectives-To test the effectiveness of the CHAMP among black South Africans in KwaZuluNatal, South Africa.Methods-A randomized control trial was conducted in KwaDedangendlale, South Africa, among youths (ages 9-13) and their families (245 intervention families rearing 281 children and 233 control families rearing 298 children). The CHAMPSA intervention targeted HIV risk behaviors by strengthening family relationship processes as well as targeting peer influences through enhancing social problem solving and peer negotiation skills for youths.Results-Among caregivers in the control and experimental conditions, significant intervention group differences were revealed regarding HIV transmission knowledge, less stigma toward HIVinfected people, caregiver monitoring-family rules, caregiver communication comfort, caregiver communication frequency and social networks. Among youths, data revealed that control and experimental groups were significantly different for children in AIDS transmission knowledge and less stigma toward HIV-infected people.Conclusions-CHAMPSA enhances a significant number individual, family and community protective factors that can help youths avoid risky behaviors leading to HIV-positive status. KeywordsSouth Africa; HIV/AIDS; prevention When the current research project began 5 years ago, South Africa had an estimated 5 million adults and children living with HIV/AIDS. 1 Despite numerous deaths, in 2005, this number had increased to an estimated 5.5 million. 2 Adolescents and young adults are at a particularly high risk of infection, as they evidence alarmingly high rates of both HIV prevalence and incidence. 3-6 For example, the HIV prevalence rate for males 15-19 years of age is 3.2%. For Send correspondence and reprint requests for J Natl Med Assoc. 2008;100:936-944 In addition to these protective factors, ethnographic information gathered to adapt CHAMP to South Africa 13-15 suggested that the dynamics of child abuse, stigma, grief from loss (from AIDS), and social capital were important risk and protective factors to consider. Thus, CHAMPSA was designed to benefit from pro-social peer and support networks by using multiple-family groups. 9,16-19Given the success of the CHAMP Family Program in the United States, 9,20 we hypothesize South-African adolescents in the CHAMPSA experimental condition will evidence enhanced outcomes on study measures relative to the youths in the comparison condition. Theoretical BasisThe Theory of Triadic Influence (TTI) 21 was used to guide the CHAMPSA program. Specifically, 7 community field principles were developed from the TTI 12,22,23 ( Figure 1) to underpin CHAMPSA. These 7 field principles were designed to guide academic/community partnerships to actualize the TTI and to base their intervention on sound scientific theory. Bell 9 suggests these 7 universal field principles of behavior change have been found to be effective in promoting resiliency and behavior change in youths in a number of communitybased projects. 12,24,25 Adaptation of CHAMP fo...
IMPORTANCE Immune checkpoint inhibitors (ICIs) and radiation therapy (RT) are widely used to treat various cancers, but little data are available to guide clinicians on ICI use sequentially with RT. OBJECTIVE To assess whether there is an increased risk of serious adverse events (AEs) associated with RT given within 90 days prior to an ICI. DESIGN, SETTING, AND PARTICIPANTS Individual patient data were pooled from 68 prospective trials of ICIs submitted in initial or supplemental licensing applications in the US Food and Drug Administration (FDA) databases through December 2019. Two cohorts were generated: (1) patients who received RT within the 90 days prior to beginning ICI therapy and (2) those who did not receive RT within the 90 days prior to beginning ICI therapy, and AE frequencies were determined. A 1:1 propensity score-matched analysis was performed.INTERVENTIONS All patients received an ICI (atezolizumab, avelumab, cemiplimab, durvalumab, ipilimumab, nivolumab, or pembrolizumab); 1733 received RT within the 90 days prior to starting ICI therapy, and 13 956 did not. MAIN OUTCOMES AND MEASURESThe primary outcome was frequency and severity of AEs. Incidence of AEs was compared descriptively between participants who did vs did not receive RT in the propensity score-matched set. Because all analyses are exploratory (ie, not preplanned and no alpha allocated), assessment for statistical significance of the differences between groups was not considered appropriate.RESULTS A total of 25 469 patients were identified; 8634 were excluded because they lacked comparators who had received RT (n = 976), did not receive an ICI (n = 4949), received RT outside of the target window (n = 2338), or had missing data in 1 or more variables used in the propensity analysis (n = 371), leaving 16 835 patients included in the analysis. The majority were younger than 65 years (9447 [56.1%]), male (10 459 [62.1%]), and White (13 422 [79.7%]). Patients receiving RT had generally similar rates of AEs overall to those patients who did not receive RT. The average absolute difference in rates across the AEs was 1.2%, and the difference ranged from 0% for neurologic AEs to 8% for fatigue. No difference in grade 3 to 4 AEs was observed between the 2 groups (absolute difference ranged from 0.01% to 2%). These findings persisted after propensity score matching. CONCLUSIONS AND RELEVANCEIn this pooled analysis, administration of an ICI within 90 days following RT did not appear to be associated with an increased risk of serious AEs. Thus, it would appear to be safe to administer an ICI within 90 days of receiving RT. These findings should be confirmed in future prospective trials.
We consider the problem of sample size determination for count data. Such data arise naturally in the context of multi-center (or cluster) randomized clinical trials, where patients are nested within research centers. We consider cluster-specific and population-average estimators (maximum likelihood based on generalized mixed-effects regression and generalized estimating equations respectively) for subject-level and cluster-level randomized designs respectively. We provide simple expressions for calculating number of clusters when comparing event rates of two groups in cross-sectional studies. The expressions we derive have closed form solutions and are based on either between-cluster variation or inter-cluster correlation for cross-sectional studies. We provide both theoretical and numerical comparisons of our methods with other existing methods. We specifically show that the performance of the proposed method is better for subject-level randomized designs, whereas the comparative performance depends on the rate ratio for the cluster-level randomized designs. We also provide a versatile method for longitudinal studies. Results are illustrated by three real data examples.
The FDA approved capmatinib and tepotinib on May 6, 2020, and February 3, 2021, respectively. Capmatinib is indicated for patients with metastatic non–small cell lung cancer (mNSCLC) whose tumors have a mutation leading to mesenchymal–epithelial transition (MET) exon 14 skipping as detected by an FDA-approved test. Tepotinib is indicated for mNSCLC harboring MET exon 14 skipping alterations. The approvals were based on trials GEOMETRY mono-1 (capmatinib) and VISION (tepotinib). In GEOMETRY mono-1, overall response rate (ORR) per Blinded Independent Review Committee (BIRC) was 68% [95% confidence interval (CI), 48–84] with median duration of response (DoR) 12.6 months (95% CI, 5.5–25.3) in 28 treatment-naïve patients and 41% (95% CI: 29, 53) with median DoR 9.7 months (95% CI, 5.5–13) in 69 previously treated patients with NSCLC with mutations leading to MET exon 14 skipping. In VISION, ORR per BIRC was 43% (95% CI: 32, 56) with median DoR 10.8 months (95% CI, 6.9–not estimable) in 69 treatment-naïve patients and 43% (95% CI, 33–55) with median DoR 11.1 months (95% CI, 9.5–18.5) in 83 previously-treated patients with NSCLC harboring MET exon 14 alterations. These are the first two therapies to be FDA approved specifically for patients with metastatic NSCLC with MET exon 14 skipping.
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