Soutinho, Gustavo

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Gustavo Domingos da Costa Coelho Soutinho Docente do Departamento de Ciência e Tecnologia da Universidade Portucalense.

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REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura. Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture. Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations: - the understanding of local, national and international environment; - the development of activities oriented to professional practice, namely in the business world.

Resultados da pesquisa

A mostrar 1 - 3 de 3
  • PublicaçãoAcesso Aberto
    Presmoothed estimators of the state occupation probabilities in multi-state survival data
    2024-06-07 - Meira-Machado, Luís; Soutinho, Gustavo
    The progress of a disease can be analyzed using multistate models. These models focus on two key parameters of interest: the transition hazard and the state occupation probabilities. The state occupation probabilities have been consistently estimated by the Aalen-Johansen estimator. This estimator is particularly well-suited for handling censoring and benefits from the Markov assumption in the underlying stochastic process. In some cases, these estimators may lead to estimators with higher variability. To mitigate this issue we propose alternative estimators that incorporate a preliminary estimation approach. We introduce also practical estimation techniques for the state occupation probabilities, considering covariate measures. We explore the finite sample behavior of the estimators through simulations. An application to breast cancer is included.
  • PublicaçãoAcesso Aberto
    Estimation of the transition probabilities conditional on covariates with repeated measures: A joint modeling approach
    2024-06-07 - Soutinho, Gustavo; Meira-Machado, Luís
    In recent years, there has been a significant urge of interest in longitudinal and survival data modeling. This approach holds particular significance in cancer research, where it enables the evaluation of how longitudinal markers influence the event of interest. This paper aims to introduce practical estimation techniques for transition probabilities, conditional on observed covariates with repeated measurements. This innovation allows us to incorporate the trajectory of longitudinal outcomes into regression models by accommodating time-varying covariates for each individual. The results presented in this study confirm the superior efficiency of the proposed methods, which merge existing approaches for joint modeling of longitudinal and survival data with the landmark approach for estimating transition probabilities. These methods outperform approaches that do not fully account the information provided by longitudinal covariate measurements.
  • PublicaçãoAcesso Restrito
    Development of a predictive score to discriminate community acquired pneumonia with underlying lung cancer: A retrospective case – control study
    2024-05-21 - Barbosa-Martins, João; Mendonça, Joana; Carvalho, Nuno; Carvalho, Carolina; Sarmento, Helena; Soutinho, Gustavo; Coutinho, Camila; Cotter, Jorge
    Background: A pneumonic infiltrate might hide an occult lung cancer (LC). This awareness depends on each clinician personal experience, turning definitive LC diagnosis challenging and possibly delayed. In this study we aimed to develop a clinical score to better identify those cases. Materials and Methods: We conducted a retrospective case–control study, including previously undiagnosed LC patients admitted in our institution, with a presumptive suspicious of community acquired pneumonia (CAP). Cases were compared with random CAP inpatient controls, using a matched 2:1 ratio. Demographic, clinical, and laboratorial variables were assessed for a possible association with the presence of a CAP with underlying LC (CAP–uLC). Results: Among 535 hospitalized LC patients, 43 cases had a presentation compatible with CAP and were compared with 86 CAP controls. A scoring system was built using 6 independent variables, which positively correlated with CAP–uLC: smoking history (OR: 8.3 [1.9–36.2]; p=0.005); absence of fever (6.5 [2.0–21.5]; p=0.002); sputum with blood (5.9 [1.2–29.9]; p=0.033); platelet count ≥ 232x103/uL (5.8 [1.6–20.6]; p=0.006); putative alternative diagnosis than CAP (4.6 [1.5–14.7]; p=0.009); and duration of symptoms ≥ 10 days (3.7 [1.1–13.0]; p=0.037). Our score presented an AUC of 0.910 (95% CI, 0.852–0.967; p<0.001), a sensitivity of 88.1% and specificity of 84.7%, in predicting the risk of presenting a CAP–uLC, when set to a cutoff of 18. ConclusionWe propose a novel risk score aimed to aid clinicians identifying patients with CAP–uLC in the acute setting, possibly prompting early LC diagnosis.