Less than whole uterus irradiation for patients with locally advanced cervical cancer.

INTRODUCTION: Current consensus guidelines for definitive cervical cancer intensity modulated radiation therapy (IMRT) recommend inclusion of the entire uterus within the clinical target volume, however this is debated. We aimed to evaluate outcomes of patients with cervical cancer who were treated with less than whole uterus irradiation. METHODS: We identified 109 patients with FIGO Stage IB-IVA cervical cancer treated definitively with concurrent chemoradiation, including IMRT and brachytherapy, from 2010 to 2022 at a single institution where the practice was to include the gross cervix tumor with an internal target volume with differences in bladder filing accounted for, plus additional 5 mm planning target volume (PTV) margin. Local, regional, and distant recurrences were analyzed using competing risk methods, and a Wilcoxon rank sum test was performed to assess differences in dose to organs at risk based on the proportion of the uterus included in the PTV, with the median proportion of the uterus included (75 %) used as the cut-point. RESULTS: The median follow-up time was 65 months (range 3-352 months). The 2-year cumulative incidence of LR for the entire cohort was 4.2 % (95 % confidence interval [CI] 1.3-9.7). Compared with patients who had ≥ 75 % of the uterus included in the PTV, patients who had < 75 % of the uterus included in the PTV had significantly lower bowel D200cc (p = 0.02). The cumulative incidence of local failure (LR) was not significantly different between the two groups. CONCLUSIONS: Including less than the whole uterus for definitive cervix cancer IMRT does not seem to compromise local control. Less than whole uterus irradiation could be considered for carefully selected cervix cancer patients to decrease bowel dose and possible treatment-related toxicity.

Modelado espacial bayesiano de la enfermedad de Chagas en la Huasteca Potosina / Bayesian spatial modeling of Chagas disease in the Huasteca Potosina

Resumen Introducción La enfermedad de Chagas es una infección sistémica, causada por el protozoario Trypanosoma cruzi. Está documentado como la influencia de factores ambientales favorecen la presencia de la infección. Objetivo Comprender los patrones de distribución espacial de riesgo y los factores ambientales y socioeconómicos que favorecen la propagación de la enfermedad de Chagas. Material y métodos Se aplicó un análisis de regresión espacial bayesiano a datos de la incidencia de la enfermedad de Chagas en la Huasteca Potosina en el periodo de 2003-2012. Resultados Se observó un patrón claro de distribución espacial en la incidencia de la enfermedad en la Huasteca Potosina, misma que se vio significativamente correlacionada en el modelo de regresión multivariante final con la temperatura mínima, los porcentajes de viviendas con piso de tierra, de viviendas sin agua entubada, de población de tres años y más que habla lengua indígena y no habla español, de población mayor a 15 años analfabeta, derechohabiente a servicios de salud, de viviendas con algún nivel de hacinamiento y de viviendas habitadas que cuentan con servicios. Conclusiones El análisis pone de manifiesto que es la población indígena la más afectada, ya que este grupo es el que más carece de acceso a servicios (salud, educación, vivienda), por lo tanto, favorece la presencia del vector causante de la enfermedad. En la Huasteca Potosina, esta población habita en zonas de difícil acceso, lo que dificulta la implementación de programas adecuados de control del vector y la infección.

Abstract Introduction Chagas disease is a systemic infection caused by the protozoan Trypanosoma cruzi. There is evidence that environmental factors favor the maintenance of the infection. Objective To understand the spatial distribution patterns of risk, and environmental and socioeconomic factors that favour the spread of Chagas disease. Material and methods Data on Chagas disease incidence in the Huasteca Potosina were collected during 2003-2012 and then analyzed by a Bayesian method of spatial regression. Results A clear pattern of spatial distribution of incidence of the disease in the Huasteca was observed, and it was significantly correlated with the final multivariate regression model using variables such as the minimum temperature, % of households with dirt floors, % of households without running water, % of population with three years and over speaking indigenous languages only, % of population over 15 years illiterate, % entitled to health care, % of households with some level of overcrowding and % of households with basic services. Conclusions The analysis showed that the indigenous population is the most affected by Chagas disease and that was related to lack to basic services (health, education, housing), therefore, those conditions favor not only the presence of the vector but also the disease. In the Huasteca, this population lives in areas of difficult access, which hinders the implementation of appropriate programs to control the vector and the infection.