High dimensional single-index mixture cure models

Programa Oficial de Doctorado en Estadística e Investigación Operativa. 5017V01[Abstract] In survival analysis, there are situations in which not all subjects are susceptible to the final event. For example, if the event is a cancer therapy-related adverse effect, there will be a fraction of patients (considered as cured) that will never experience it. Mixture cure models allow to estimate the probability of cure and the survival function for the uncured subjects. In the literature, nonparametric estimation of both functions is limited to continuous univariate covariates. We fill this gap by proposing single-index mixture cure models. They allow working with a vector covariate and assume that the survival function depends on it through an unknown linear combination, that is estimated by maximum likelihood. Besides, a nonparametric estimator for the density function of the uncured individuals is introduced, and its iid representation is derived. Finally, the proposed models are extended to functional covariates and a preprocessing algorithm is implemented to deal with medical images. The methodology is applied to a cardiotoxicity dataset. The goal is to determine whether (and how) certain factors affect the probability of experiencing the cardiovascular problem and the amount of time it takes for it to manifest. Understanding risk factors may lead to a patient-based preventive medicine.[Resumen] En análisis de supervivencia hay situaciones en las cuales no todos los sujetos son susceptibles al evento final. Por ejemplo, si el evento es un efecto adverso de una terapia oncológica, habrá pacientes (considerados como curados) que nunca lo experimentarán. Los modelos de curación de tipo mixtura permiten estimar la probabilidad de curación y la función de supervivencia de los sujetos susceptibles. En la literatura, la estimaciuñin no paramétrica de ambas funciones se limita a covariables unidimensionales. En esta tesis se proponen los modelos single-index de curación de tipo mixtura. Estos permiten trabajar con una covariable vectorial y asumen que la función de supervivencia depende de ella mediante una combinación lineal que se puede estimar por máxima verosimilitud. Además, se introduce un estimador no paramétrico para la funci´on de densidad de los susceptibles y se obtiene su representación iid. Finalmente, los modelos propuestos se extienden a covariables funcionales y se implementa un algoritmo de preprocesamiento de imágenes médicas. La metodología se aplica a datos de cardiotoxicidad con el objetivo de determinar qué factores afectan (y cómo) a la probabilidad de experimentarla y al tiempo que tarda en manifestarse. Conocer los factores de riesgo podría conducir a una medicina preventiva personalizada.[Resumo] En análise de supervivencia hai situacións nas que non todos os individuos son susceptibles ao evento final. Por exemplo, se o evento é un efecto adverso dunha terapiaoncolóxica, haberá pacientes (considerados como curados) que nunca o experimentarán. Os modelos de curaci´on de tipo mestura permiten estimar a probabilidade de curación e a función de supervivencia dos suxeitos susceptibles. Na literatura, a estimación non paramétrica destas dúas funcións limítase a covariables unidimensionais. Nesta tese propóñense os modelos single-index de curación de tipo mestura. Estes permiten traballar cunha covariable vectorial e asumen que a función de supervivencia depende dela mediante unha combinación lineal que se pode estimar por máxima verosimilitude. Ademais, introd´ucese un estimador non paramétrico para a función de densidade dos susceptibles e obtense a súa representación iid. Finalmente, os modelos propostos esténdense a covariables funcionais e impleméntase un algoritmo de preprocesamento de imaxes médicas. A metodoloxía aplícase a datos de cardiotoxicidade co obxectivo de determinar que factores afectan (e como) á probabilidade de experimentala e ao tempo que tarda en manifestarse. Coñecer os factores de risco podería conducir cara unha medicina preventiva personalizada.Xunta de Galicia; ED431C 2020/14Xunta de Galicia; ED431G 2019/01Xunta de Galicia; ED481A-2020/290This research has been partially supported by MINECO (Ministerio de Economía y Competitividad) Grant MTM2017-82724-R, by Ministerio de Ciencia e Innovación under grant PID2020-113578RB-100 and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C 2020/14 and Centro de Investigación del Sistema Universitario de Galicia ED431G 2019/01), all of them through the ERDF (European Regional Development Fund). The doctoral student acknowledges financial support from Axudas Predoutorais da Xunta de Galicia, with reference ED481A-2020/290. The work has been partially carried out during two visits at École Nationale de la Statistique et de l’Analyse de l’Information (ENSAI) and Katholieke Universiteit Leuven. The first stay was funded through grant ED481A-2020/290 and the second one was supported by the research group MODES (Modelización, Optimización e Inferencia Estadística) and CITIC (Centro de Investigación de Tecnologías de la Información y de la Comunicación)

Preliminary evaluation of pressurized hot water extraction for the solubilization of valuable components from hospital kitchen wastes

An alternative to mitigate the environmental impact of food waste is the separation of valuable components. Due to the difficulty and heterogeneity of such wastes, the study of model systems allowing a regular and predictable production and composition was used. A mixture of pre- and post-consumption kitchen wastes from a hospital with an automated organic matter segregation and drying system (HKW) has been collected to obtain representative samples of the different diets prepared daily. The chemical characterization of streams revealed a variation in composition of the wastes depending on the menus. Those from dinner + breakfast (D + B) presented protein content in the range 42–54% of the dry weight and those form lunch + snack (L + S) in the range 19–33%, whereas the carbohydrate content was 52–65% in D + B and 47–53% in L + S waste streams. These values suggested the possibility of proposing a different valorization scheme for each type of stream. In this study, a green extraction process with pressurized hot water under microwave heating has been explored for the solubilization of the most abundant and valuable components, protein, and carbohydrates. The starch fractions recovered from the crude extract were proposed for the formulation of anti-freezing hydrogels suitable for 3D printing, and the possibilities of valorizing other fractions such as proteins as plant biostimulants are also discussed.Xunta de Galicia | Ref. ED431F 2020/01Xunta de Galicia | Ref. ED431G2019/06Agencia Estatal de Investigación | Ref. RYC2018-024454-IUniversidade de Vigo/CISU

XVI Congreso Galego de Estatística e Investigación de Operacións ; I Xornadas Innovación Docente na Estatística e Investigación de Operacións : libro de actas

O presente libro de actas recolle o resumo das catro conferencias plenarias e os 56 traballos presentados: 41 comunicacións orais, das que 9 son traballos que optan ao premio a investigadores novos e 3 son traballos presentados na sesión de biometría que organizan conxuntamente a SGAPEIO e a Sociedade Portuguesa de Estatística (SPE); 11 pósteres e 4 comunicacións orais nas xornadas de innovación docente

BC_cardiotox: A cardiotoxicity dataset for breast cancer patients

The BC_cardiotox database is a result of the collaboration between the University of A Coruña and the University Hospital of A Coruña. It contains information about 531 breast cancer patients and aims to enable the scientific community in conducting new research on cancer therapy-related cardiac dysfunction (CTRCD). The development of this side effect has important clinical and prognostic implications, and the availability of good predictors may allow its early detection. Although some risk factors are known, they are not sufficient to predict which patients will develop CTRCD during treatment. Therefore, in clinical practice it is recommended to monitor the appearance of CTRCD through blood laboratory tests and cardiac imaging tests. The echocardiogram, which allows to assess various parameters of the structure and function of the heart, is the main diagnostic tool. The Tissue Doppler Imaging (TDI), which shows the velocity of contraction and relaxation of the cardiac muscle, can be obtained by using this technique. This information, measured before treatment, may help in the early identification of CTRCD. Since the TDI shows a velocity as a function of time, it can be preprocessed to obtain a functional datum. For each patient, baseline clinical variables related to anthropometric and heart measures are available, as well as the preprocessed baseline TDI. The code for the preprocessing of image data is also provided, together with two TDI images for reproducibility issues. The code is implemented in the statistical software R. Corresponding author: Beatriz Piñeiro-Lamas ([email protected] / [email protected])</p

A cardiotoxicity dataset for breast cancer patients

Abstract This dataset is a result of the collaboration between the University of A Coruña and the University Hospital of A Coruña. It contains information about 531 women diagnosed with HER2+ breast cancer, treated with potentially cardiotoxic oncologic therapies. These treatments can cause cardiovascular adverse events, including cardiac systolic dysfunction, the development of which has important clinical and prognostic implications. The availability of good predictors may enable early detection of these cardiac problems. Variables such as age, weight and height are available for each patient, as well as some measures obtained from echocardiography, a technique used prior and during the treatment to check the structure and function of the heart. Among them, there is a functional variable that measures the myocardial velocity during the cardiac cycle. For patients that experienced cancer therapy-related cardiac dysfunction during the treatment period, time until its appearance is known. This dataset aims to enable the scientific community in conducting new research on this cardiovascular side effect

Bacteremia nosocomial asociada a catéter vascular central en unidades de cuidados intensivos en 2 hospitales en Galicia (España)

Fundamento y objetivo: Las infecciones asociadas a la asistencia sanitaria suponen una parte sustancial de los efectos adversos que los pacientes sufren durante la atención médica. Las bacteremias asociadas a catéter vascular central (CVC) suponen una causa importante de estas infecciones. Los objetivos fueron determinar la tasa de incidencia de bacteremia asociada a CVC en unidades de cuidados intensivos y la identificación de los principales factores de riesgo involucrados en el desarrollo de bacteremia asociada a CVC. Sujetos y métodos: El estudio se llevó a cabo en 2 hospitales de Galicia (España) y se realizó un estudio de cohorte o incidencia y posteriormente, anidado en este, un subestudio de casos y controles. Se incluyeron a pacientes atendidos en unidades de cuidados intensivos de 2 hospitales (hospital A y hospital B) durante un período de 2 meses, de los años 2009, 2010 y 2011. Se calcularon las tasas de incidencia y los factores de riesgo asociados al desarrollo de bacteremia asociada a CVC. Resultados: Las tasas de incidencia encontradas fueron 3,21; 2,91 y 5,76 bacteremias por 1.000 días en riesgo para el hospital A para los años 2009, 2010 y 2011 respectivamente. Estas tasas fueron de 2,10; 0 y 4,74 bacteremias por 1.000 días en riesgo para el hospital B para los mismos años. Se identificaron como factores de riesgo, el estado de coma (OR = 3,72; IC95% 1,06-13,02) y el número de catéteres (OR = 1,90; IC95% 1,21-2,97). Conclusiones: Se observan tasas superiores al estándar recomendado en la mayoría de los períodos de estudio. Se debe prestar especial atención a los pacientes en coma y con varios catéteres, al presentar estos un riesgo mayor de desarrollo de bacteremias asociadas a CVC

X-ray cross-complementing group 1 and thymidylate synthase polymorphisms might predict response to chemoradiotherapy in rectal cancer patients

Purpose: 5-Fluorouracil-based chemoradiotherapy before total mesorectal excision is currently the standard treatment of Stage II and III rectal cancer patients. We used known predictive pharmacogenetic biomarkers to identify the responders to preoperative chemoradiotherapy in our series. Methods and Materials: A total of 93 Stage II-III rectal cancer patients were genotyped using peripheral blood samples. The genes analyzed were X-ray cross-complementing group 1 (XRCC1), ERCC1, MTHFR, EGFR, DPYD, and TYMS. The patients were treated with 225 mg/m2/d continuous infusion of 5-fluorouracil concomitantly with radiotherapy (50.4 Gy) followed by total mesorectal excision. The outcomes were measured by tumor regression grade (TRG) as a major response (TRG 1 and TRG 2) or as a poor response (TRG3, TRG4, and TRG5). Results: The major histopathologic response rate was 47.3%. XRCC1 G/G carriers had a greater probability of response than G/A carriers (odds ratio, 4.18; 95% confidence interval, 1.62-10.74, p =.003) Patients with polymorphisms associated with high expression of thymidylate synthase (2R/3G, 3C/3G, and 3G/3G) showed a greater pathologic response rate compared with carriers of low expression (odds ratio, 2.65; 95% confidence interval, 1.10-6.39, p =.02) No significant differences were seen in the response according to EGFR, ERCC1, MTHFR-C677 and MTHFR-A1298 expression. Conclusions: XRCC1 G/G and thymidylate synthase (2R/3G, 3C/3G, and 3G/3G) are independent factors of a major response. Germline thymidylate synthase and XRCC1 polymorphisms might be useful as predictive markers of rectal tumor response to neoadjuvant chemoradiotherapy with 5-fluorouracil