Metastatic melanoma positively influences pregnancy outcome in a mouse model: could a deadly tumor support embryo life?

The incidence of melanoma is increasing worldwide. It is one of the leading cancers in pregnancy and the most common malignancy to metastasize to placenta and fetus. There are no publications about experimental models of melanoma and pregnancy. We propose a new experimental murine model to study the effects of melanoma on pregnancy and its metastatic process. We tested several doses of melanoma cells until we arrived at the optimal dose, which produced tumor growth and allowed animal survival to the end of pregnancy. Two control groups were used: control (C) and stress control (SC) and three different routes of inoculation: intravenous (IV), intraperitoneal (IP) and subcutaneous (SC). All the fetuses and placentas were examined macroscopically and microscopically. The results suggest that melanoma is a risk factor for intrauterine growth restriction but does not affect placental weight. When inoculated by the SC route, the tumor grew only in the site of implantation. The IP route produced peritoneal tumoral growth and also ovarian and uterine metastases in 60% of the cases. The IV route produced pulmonary tumors. No placental or fetal metastases were obtained, regardless of the inoculation route. The injection of melanoma cells by any route did not increase the rate of fetal resorptions. Surprisingly, animals in the IV groups had no resorptions and a significantly higher number of fetuses. This finding may indicate that tumoral factors released in the host organism to favor tumor survival may also have a pro-gestational action and consequently improve the reproductive performance of these animals.

A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes

We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, for a given vector of covariates. Approaches based on semiparametric and parametric (exponential and Weibull distributions) methodologies are considered. A simulation study is conducted to evaluate the performance of the proposed estimator and the jackknife resampling method is used to estimate the variance of such estimator. An application to a real data set is also included.