RESUMEN
A standard competing risks set-up requires both time to event and cause of failure to be fully observable for all subjects. However, in application, the cause of failure may not always be observable, thus impeding the risk assessment. In some extreme cases, none of the causes of failure is observable. In the case of a recurrent episode of Plasmodium vivax malaria following treatment, the patient may have suffered a relapse from a previous infection or acquired a new infection from a mosquito bite. In this case, the time to relapse cannot be modeled when a competing risk, a new infection, is present. The efficacy of a treatment for preventing relapse from a previous infection may be underestimated when the true cause of infection cannot be classified. In this paper, we developed a novel method for classifying the latent cause of failure under a competing risks set-up, which uses not only time to event information but also transition likelihoods between covariates at the baseline and at the time of event occurrence. Our classifier shows superior performance under various scenarios in simulation experiments. The method was applied to Plasmodium vivax infection data to classify recurrent infections of malaria.
RESUMEN
We consider a specific situation of correlated data where multiple outcomes are repeatedly measured on each member of a couple. Such multivariate longitudinal data from couples may exhibit multi-faceted correlations which can be further complicated if there are polygamous partnerships. An example is data from cohort studies on human papillomavirus (HPV) transmission dynamics in heterosexual couples. HPV is a common sexually transmitted disease with 14 known oncogenic types causing anogenital cancers. The binary outcomes on the multiple types measured in couples over time may introduce inter-type, intra-couple, and temporal correlations. Simple analysis using generalized estimating equations or random effects models lacks interpretability and cannot fully utilize the available information. We developed a hybrid modeling strategy using Markov transition models together with pairwise composite likelihood for analyzing such data. The method can be used to identify risk factors associated with HPV transmission and persistence, estimate difference in risks between male-to-female and female-to-male HPV transmission, compare type-specific transmission risks within couples, and characterize the inter-type and intra-couple associations. Applying the method to HPV couple data collected in a Ugandan male circumcision (MC) trial, we assessed the effect of MC and the role of gender on risks of HPV transmission and persistence.
RESUMEN
OBJECTIVE: Clinical validation of a chemoresponse assay was recently published, demonstrating a significant increase in overall survival in recurrent ovarian cancer patients treated with therapies to which their tumor was sensitive in the assay. The current study investigates the cost effectiveness of using the assay at the time of ovarian cancer recurrence from the payer's perspective. METHODS: Using a Markov state transition model, patient characteristics and survival data from the recent clinical study, the cumulative costs over the study horizon (71 months) for both the baseline (no assay) and intervention (assay consistent, hypothetical) cohorts were evaluated. RESULTS: The assay consistent cohort had an incremental cost effectiveness ratio (ICER) of $6206 per life year saved (LYS), as compared to the baseline cohort. Cost-effectiveness was further demonstrated in platinum-sensitive and platinum-resistant populations treated with assay-sensitive therapies, with ICERs of $2773 per LYS and $2736 per LYS, respectively. CONCLUSIONS: The use of a chemoresponse assay to inform treatment decisions in recurrent ovarian cancer patients has the potential to be cost-effective in both platinum-sensitive and platinum-resistant patients.