Neoadjuvant chemoimmunotherapy shows major pathological response and low recurrence in head and neck squamous cell carcinoma.

BACKGROUND: The study aimed to investigate the efficacy and survival outcomes of neoadjuvant chemotherapy combined with programmed cell death protein 1 (PD-1) blockade (neoadjuvant chemoimmunotherapy) for patients with resectable head and neck squamous cell carcinoma (HNSCC). METHODS: A retrospective analysis was conducted. Patients with initially diagnosed, resectable HNSCCs who received the neoadjuvant chemoimmunotherapy and radical surgery were included. Correlation analysis between patients' clinical characteristics and pathological responses, and survival analysis were performed. RESULTS: A total of 79 patients were included. The majority of patients (55, 69.6%) were diagnosed at locally advanced stages and most of them (58, 73.4%) had tumor located at the oral cavity. Nearly half of patients (35, 44.3%) received two cycles of neoadjuvant chemoimmunotherapy and the rest had three or more cycles. The R0 resection rate was 98.7%. In the pathological evaluation, 53.1% of patients reached pathological complete responses or major pathological responses. After a median follow-up of 17.0 months, the 1-year disease-free survival (DFS) and overall survival (OS) rates were 87.2% and 97.4%, respectively. The pathological response showed a significantly positive association with survival benefits (p < 0.001). Patients with human papillomavirus (HPV)-positive oropharyngeal cancer had the best pathological response and survival outcomes. Besides, history of radiation at head and neck region and poor pathological response were found to be independent risk factors of DFS for patients receiving such treatments. CONCLUSION: Neoadjuvant chemoimmunotherapy of HNSCC showed high rate of pathological response and low recurrence rate, holding promise for becoming the new standard of care for resectable HNSCC.

Assessing dengue fever risk in Costa Rica by using climate variables and machine learning techniques.

Dengue fever is a vector-borne disease affecting millions yearly, mostly in tropical and subtropical countries. Driven mainly by social and environmental factors, dengue incidence and geographical expansion have increased in recent decades. Therefore, understanding how climate variables drive dengue outbreaks is challenging and a problem of interest for decision-makers that could aid in improving surveillance and resource allocation. Here, we explore the effect of climate variables on relative dengue risk in 32 cantons of interest for public health authorities in Costa Rica. Relative dengue risk is forecast using a Generalized Additive Model for location, scale, and shape and a Random Forest approach. Models use a training period from 2000 to 2020 and predicted climatic variables obtained with a vector auto-regressive model. Results show reliable projections, and climate variables predictions allow for a prospective instead of a retrospective study.

Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica.

Objective: To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods: Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results: The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions: Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning.

Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica

[ABSTRACT]. Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results. The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions. Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning.

[RESUMEN]. Objetivo. Resumir los resultados de las investigaciones realizadas en Costa Rica en las que se aplicaron métodos matemáticos y estadísticos para estudiar la dinámica de transmisión de las enfermedades transmitidas por mosquitos. Métodos. Se seleccionaron y analizaron tres artículos con análisis matemáticos y estadísticos sobre enfermedades transmitidas por vectores en Costa Rica. En estos artículos se muestra el valor y la pertinencia de emplear diferentes métodos cuantitativos para comprender la dinámica de la enfermedad y brindar apoyo a la toma de decisiones. Resultados. Los resultados de estas investigaciones: 1) muestran la repercusión en los informes de casos de dengue cuando surge un segundo agente patógeno, como el chikunguña; 2) recuperan parámetros clave en la dinámica del Zika mediante la inferencia bayesiana; y 3) muestran el uso de los algoritmos de aprendizaje automático y las variables climáticas para pronosticar el riesgo relativo de dengue en cinco lugares diferentes. Conclusiones. Los modelos matemáticos y estadísticos permiten describir la dinámica de transmisión de las enfermedades transmitidas por mosquitos, mediante la provisión de información cuantitativa para brindar apoyo a los métodos de prevención y control y a la planificación de la asignación de recursos.

[RESUMO]. Objetivo. Resumir os resultados de estudos realizados na Costa Rica em que foram aplicados métodos matemáticos e estatísticos para estudar a dinâmica de transmissão de doenças transmitidas por mosquitos. Métodos. Foram selecionados e revisados três artigos com análises matemáticas e estatísticas sobre doenças transmitidas por vetores na Costa Rica. Esses artigos mostram o valor e a pertinência do uso de diferentes métodos quantitativos para compreender a dinâmica das doenças e apoiar a tomada de decisões. Resultados. Os resultados dessas investigações: 1) mostram o impacto nas notificações de casos de dengue quando surge um segundo patógeno, como o chikungunya; 2) recuperam parâmetros-chave na dinâmica do zika, usando a inferência bayesiana; e 3) mostram o uso de algoritmos de aprendizagem por máquina e variáveis climáticas para prever o risco relativo da dengue em cinco locais diferentes. Conclusões. A modelagem matemática e estatística permite a descrição da dinâmica de transmissão de doenças transmitidas por mosquitos ao oferecer informações quantitativas para apoiar métodos de prevenção e/ou controle e o planejamento da alocação de recursos.

Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica / Modelos matemáticos y estadísticos para el control de enfermedades transmitidas por mosquitos: la experiencia de Costa Rica / Modelos matemáticos e estatísticos para o controle de doenças transmitidas por mosquitos: a experiência da Costa Rica

ABSTRACT Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results. The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions. Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning.

RESUMEN Objetivo. Resumir los resultados de las investigaciones realizadas en Costa Rica en las que se aplicaron métodos matemáticos y estadísticos para estudiar la dinámica de transmisión de las enfermedades transmitidas por mosquitos. Métodos. Se seleccionaron y analizaron tres artículos con análisis matemáticos y estadísticos sobre enfermedades transmitidas por vectores en Costa Rica. En estos artículos se muestra el valor y la pertinencia de emplear diferentes métodos cuantitativos para comprender la dinámica de la enfermedad y brindar apoyo a la toma de decisiones. Resultados. Los resultados de estas investigaciones: 1) muestran la repercusión en los informes de casos de dengue cuando surge un segundo agente patógeno, como el chikunguña; 2) recuperan parámetros clave en la dinámica del Zika mediante la inferencia bayesiana; y 3) muestran el uso de los algoritmos de aprendizaje automático y las variables climáticas para pronosticar el riesgo relativo de dengue en cinco lugares diferentes. Conclusiones. Los modelos matemáticos y estadísticos permiten describir la dinámica de transmisión de las enfermedades transmitidas por mosquitos, mediante la provisión de información cuantitativa para brindar apoyo a los métodos de prevención y control y a la planificación de la asignación de recursos.

RESUMO Objetivo. Resumir os resultados de estudos realizados na Costa Rica em que foram aplicados métodos matemáticos e estatísticos para estudar a dinâmica de transmissão de doenças transmitidas por mosquitos. Métodos. Foram selecionados e revisados três artigos com análises matemáticas e estatísticas sobre doenças transmitidas por vetores na Costa Rica. Esses artigos mostram o valor e a pertinência do uso de diferentes métodos quantitativos para compreender a dinâmica das doenças e apoiar a tomada de decisões. Resultados. Os resultados dessas investigações: 1) mostram o impacto nas notificações de casos de dengue quando surge um segundo patógeno, como o chikungunya; 2) recuperam parâmetros-chave na dinâmica do zika, usando a inferência bayesiana; e 3) mostram o uso de algoritmos de aprendizagem por máquina e variáveis climáticas para prever o risco relativo da dengue em cinco locais diferentes. Conclusões. A modelagem matemática e estatística permite a descrição da dinâmica de transmissão de doenças transmitidas por mosquitos ao oferecer informações quantitativas para apoiar métodos de prevenção e/ou controle e o planejamento da alocação de recursos.