Univariate parametric survival analysis using GS-distributions.

The GS-distribution is a family of distributions that provide an accurate representation of any unimodal univariate continuous distribution. In this contribution we explore the utility of this family as a general model in survival analysis. We show that the survival function based on the GS-distribution is able to provide a model for univariate survival data and that appropriate estimates can be obtained. We develop some hypotheses tests that can be used for checking the underlying survival model and for comparing the survival of different groups.Peer Reviewe

Assessment of the effects of decision aids about breast cancer screening: a systematic review and meta-analysis

Objective: The aim of this systematic review and meta-analysis of randomised controlled trials (RCTs) and observational studies is to assess the effect of decision aids (DAs) in women aged 50 and below facing the decision to be screened for breast cancer. Setting: Screening for breast cancer. Intervention: DAs aimed to help women make a deliberative choice regarding participation in mammography screening by providing information on the options and outcomes. Eligible studies: We included published original, non-pilot, studies that assess the effect of DAs for breast cancer screening. We excluded the studies that evaluated only participation intention or actual uptake. The studies' risk of bias was assessed with the Cochrane Collaboration's tool for RCTs and the National Institutes of Health Quality Assessment Tool for non-RCTs. Primary and secondary outcomes: The main outcome measures were informed choice, decisional conflict and/or confidence, and knowledge. Secondary outcomes were values, attitudes, uncertainty and intention to be screened. Results: A total of 607 studies were identified, but only 3 RCTs and 1 before-after study were selected. The use of DAs increased the proportion of women making an informed decision by 14%, 95% CI (2% to 27%) and the proportion of women with adequate knowledge by 12%, 95% CI (7% to 16%). We observed heterogeneity among the studies in confidence in the decision. The meta-analysis of the RCTs showed a significant decrease in confidence in the decision and in intention to be screened. Conclusions: Tools to aid decision making in screening for breast cancer improve knowledge and promote informed decision; however, we found divergent results on decisional conflict and confidence in the decision. Under the current paradigm change, which favours informed choice rather than maximising uptake, more research is necessary for the improvement of DAs

Informed choice in breast cancer screening: the role of education

[spa ] Objetivo: Evaluar el efecto de recibir información sobre los beneficios y los efectos adversos del cribado del cáncer de mama en la elección informada, en función del nivel educativo. Método: Análisis secundario de un estudio experimental aleatorizado y controlado, en cuatro programas de cribado en Cataluña˜ y Canarias. Se analizaron 400 mujeres que iban a ser invitadas a participar por primera vez. El grupo de intervención recibió una herramienta informativa que mostraba los beneficios y los efectos adversos del cribado. El grupo control recibió un folleto estándar que recomendaba participar en el cribado. El nivel de estudios se agrupó en dos categorías: bajo y alto. La variable principal fue la elección informada definida como un conocimiento adecuado y la concordancia entre las actitudes y las intenciones. Resultados: La intervención produjo un mayor aumento del conocimiento en las mujeres con nivel educativo alto respecto a las de menor nivel educativo. Entre las mujeres que recibieron la intervención, la elección informada fue casi tres veces superior en las de nivel educativo alto (27% vs. 11%). No se observaron diferencias entre niveles educativos en los grupos de intervención y control en cuanto a conflicto decisional, confianza en la decisión, ansiedad y preocupación por el cáncer de mama. Conclusiones: Una herramienta informativa para el cribado del cáncer de mama tuvo mucho más impacto sobre la elección informada en las mujeres con nivel educativo alto. En aquellas con nivel educativo bajo mejoró la actitud frente al cribado y produjo un aumento en la intención de participar en él. [eng] Conclusions: A decision aid for breast cancer screening had much more impact on informed choice among women with a high educational level. In women with low educational level, the attitude towards screening improved and there was an increase in the intention to be screened. Objective: To evaluate the effect of receiving information about the benefits and harms of breast cancer screening in informed choice, according to educational level. Method: Secondary analysis of a randomized, controlled study, in four screening programs, in Catalonia and the Canary Islands (Spain). We analyzed 400 women who were going to be invited to participate for the first time. The intervention group received a decision aid that showed the benefits and harms of screening. The control group received a standard brochure that recommended participating in the screening program. Educational level was grouped into two categories, low and high. The primary out- come was informed choice defined as adequate knowledge and consistency between attitudes and intentions. Results: The intervention produced a greater increase in knowledge in women with a high educational level compared to those with a lower educational level. Among women who received the intervention, informed choice was almost three times higher in those with a high educational level (27% versus 11%). No differences were observed between educational levels in decisional conflict, confidence in the decision, anxiety and worry about breast cancer, in the intervention and control groups

Competing risks to breast cancer mortality in Catalonia

Background: Breast cancer mortality has experienced important changes over the last century. Breast cancer occurs in the presence of other competing risks which can influence breast cancer incidence and mortality trends. The aim of the present work is: 1) to assess the impact of breast cancer deaths among mortality from all causes in Catalonia (Spain), by age and birth cohort and 2) to estimate the risk of death from other causes than breast cancer, one of the inputs needed to model breast cancer mortality reduction due to screening or therapeutic interventions. Methods: The multi-decrement life table methodology was used. First, all-cause mortality probabilities were obtained by age and cohort. Then mortality probability for breast cancer was subtracted from the all-cause mortality probabilities to obtain cohort life tables for causes other than breast cancer. These life tables, on one hand, provide an estimate of the risk of dying from competing risks, and on the other hand, permit to assess the impact of breast cancer deaths on all-cause mortality using the ratio of the probability of death for causes other than breast cancer by the all-cause probability of death. Results: There was an increasing impact of breast cancer on mortality in the first part of the 20(th) century, with a peak for cohorts born in 1945-54 in the 40-49 age groups (for which approximately 24% of mortality was due to breast cancer). Even though for cohorts born after 1955 there was only information for women under 50, it is also important to note that the impact of breast cancer on all-cause mortality decreased for those cohorts. Conclusion: We have quantified the effect of removing breast cancer mortality in different age groups and birth cohorts. Our results are consistent with US findings. We also have obtained an estimate of the risk of dying from competing-causes mortality, which will be used in the assessment of the effect of mammography screening on breast cancer mortality in Catalonia

Assessing the impact of early detection biases on breast cancer survival of Catalan women

Survival estimates for women with screen-detected breast cancer are affected by biases specific to early detection. Lead-time bias occurs due to the advance of diagnosis, and length-sampling bias because tumors detected on screening exams are more likely to have slower growth than tumors symptomatically detected. Methods proposed in the literature and simulation were used to assess the impact of these biases. If lead-time and length-sampling biases were not taken into account, the median survival time of screen-detected breast cancer cases may be overestimated by 5 years and the 5-year cumulative survival probability by between 2.5 to 5 percent units

Competing risks to breast cancer mortality in Catalonia

Background: Breast cancer mortality has experienced important changes over the last century. Breast cancer occurs in the presence of other competing risks which can influence breast cancer incidence and mortality trends. The aim of the present work is: 1) to assess the impact of breast cancer deaths among mortality from all causes in Catalonia (Spain), by age and birth cohort and 2) to estimate the risk of death from other causes than breast cancer, one of the inputs needed to model breast cancer mortality reduction due to screening or therapeutic interventions. Methods: The multi-decrement life table methodology was used. First, all-cause mortality probabilities were obtained by age and cohort. Then mortality probability for breast cancer was subtracted from the all-cause mortality probabilities to obtain cohort life tables for causes other than breast cancer. These life tables, on one hand, provide an estimate of the risk of dying from competing risks, and on the other hand, permit to assess the impact of breast cancer deaths on all-cause mortality using the ratio of the probability of death for causes other than breast cancer by the all-cause probability of death. Results: There was an increasing impact of breast cancer on mortality in the first part of the 20th century, with a peak for cohorts born in 1945–54 in the 40–49 age groups (for which approximately 24% of mortality was due to breast cancer). Even though for cohorts born after 1955 there was only information for women under 50, it is also important to note that the impact of breast cancer on all-cause mortality decreased for those cohorts. Conclusion: We have quantified the effect of removing breast cancer mortality in different age groups and birth cohorts. Our results are consistent with US findings. We also have obtained an estimate of the risk of dying from competing-causes mortality, which will be used in the assessment of the effect of mammography screening on breast cancer mortality in Catalonia

Bayesian joint ordinal and survival modeling for breast cancer risk assessment

We propose a joint model to analyze the structure and intensity of the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model. Time-to-event is modeled through a left-truncated proportional-hazards model, which incorporates information of the longitudinal marker as well as baseline covariates. Both longitudinal and survival processes are connected by means of a common vector of random effects. General inferences are discussed under the Bayesian approach and include the posterior distribution of the probabilities associated to each longitudinal category and the assessment of the impact of the baseline covariates and the longitudinal marker on the hazard function. The flexibility provided by the joint model makes possible to dynamically estimate individual event-free probabilities and predict future longitudinal marker values. The model is applied to the assessment of breast cancer risk in women attending a population-based screening program. The longitudinal ordinal marker is mammographic breast density measured with the Breast Imaging Reporting and Data System (BI-RADS) scale in biennial screening exams. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.Peer ReviewedPostprint (author's final draft

Joint modelling analysis of prostate cancer incidence: frequentist and bayesian approaches

Prostate specific antigen (PSA) is a biomarker for prostate cancer (PCa) that is widely used for PCa screening. Using a database of 2415 men included in the Spanish screening arm of the ERSPC Study, we will use joint modelling strategies to analyze if longitudinal PSA profiles and time to PCa incidence allow to obtain a better estimate of the individual risk of PCa. Conclusions and limitations of the study will be discussed.Peer ReviewedPostprint (published version