RESUMO
A common phenomenon in cancer syndromes is for an individual to have multiple primary cancers (MPC) at different sites during his/her lifetime. Patients with Li-Fraumeni syndrome (LFS), a rare pediatric cancer syndrome mainly caused by germline TP53 mutations, are known to have a higher probability of developing a second primary cancer than those with other cancer syndromes. In this context, it is desirable to model the development of MPC to enable better clinical management of LFS. Here, we propose a Bayesian recurrent event model based on a non-homogeneous Poisson process in order to obtain penetrance estimates for MPC related to LFS. We employed a familywise likelihood that facilitates using genetic information inherited through the family pedigree and properly adjusted for the ascertainment bias that was inevitable in studies of rare diseases by using an inverse probability weighting scheme. We applied the proposed method to data on LFS, using a family cohort collected through pediatric sarcoma patients at MD Anderson Cancer Center from 1944 to 1982. Both internal and external validation studies showed that the proposed model provides reliable penetrance estimates for MPC in LFS, which, to the best of our knowledge, have not been reported in the LFS literature.
Assuntos
Síndrome de Li-Fraumeni/epidemiologia , Modelos Teóricos , Neoplasias Primárias Múltiplas/epidemiologia , Teorema de Bayes , Predisposição Genética para Doença , Humanos , Síndrome de Li-Fraumeni/genética , Modelos Genéticos , Neoplasias Primárias Múltiplas/genética , Linhagem , Penetrância , RecidivaRESUMO
Sample size calculations for trials with time-to-event outcomes are usually based on the assumption that an event - prototypically death in survival analysis - occurs only once per sample unit. However, events like changes in disease status or switches between treatment modalities may repeat over time. In trials with such outcomes, standard sample size formulae derived from the classical survival time models are not applicable. Instead, modeling the repeating transition events must precede the actual sample size calculation. Markov chains are an obvious choice to model transitions. Accordingly, in order to determine the sample size for a one-arm feasibility and acceptability study of a new drug intake route, we model switches of administration routes by a homogeneous finite-state, higher-order Markov chain. Assumptions about its transition matrix translate into multinomial distributions of the preferred administration routes at given points in time. From these distributions, the required sample size can then be calculated according to the study's specific question. In this manuscript, we first introduce the method for the case of drug intake preferences, before we briefly discuss how the proposed method can also be used for power-based sample size calculation in multi-arm trials.
Assuntos
Heroína , Projetos de Pesquisa , Humanos , Cadeias de Markov , Tamanho da Amostra , Análise de SobrevidaRESUMO
BACKGROUND: Little is known about opioid prescribing among individuals who have survived cancer. Our aim is to examine a predominantly socio-economically disadvantaged population for differences in opioid prescribing rates among cancer survivors compared with matched controls without a prior diagnosis of cancer. METHODS: This was a retrospective population-wide matched cohort study. Starting in 2010, individuals residing in Ontario, Canada, who were 18 to 64 years of age and at least 5 years past their cancer diagnosis were matched to controls without a prior cancer diagnosis based on sex and calendar year of birth. Follow-up was terminated at any indication of cancer recurrence, second malignancy, or new cancer diagnosis. To examine the association between survivorship and the rate of opioid prescriptions, an Andersen-Gill recurrent event regression model was implemented, adjusting for numerous individual-level characteristics and also accounting for the matched design. RESULTS: The rate of opioid prescribing was 1.22 times higher among survivors than among their corresponding matched controls (adjusted relative rate, 1.22; 95% CI, 1.11-1.34). Individuals from lower income quintiles who were younger, were from rural neighborhoods, and had more comorbidities had significantly higher prescribing rates. Sex was not associated with prescribing rates. This increased rate of opioid prescribing was also seen among survivors who were 10 or more years past their cancer diagnosis (compared with their controls). CONCLUSION: This study demonstrates substantially higher opioid prescribing rates among cancer survivors, even long after attaining survivorship. This raises concerns about the diagnosis and management of chronic pain problems among survivors stemming from their cancer diagnosis or treatment. Cancer 2017;123:4286-4293. © 2017 American Cancer Society.
Assuntos
Analgésicos Opioides/uso terapêutico , Prescrições de Medicamentos/estatística & dados numéricos , Neoplasias , Sobreviventes/estatística & dados numéricos , Adulto , Fatores Etários , Comorbidade , Feminino , Humanos , Renda/estatística & dados numéricos , Masculino , Análise por Pareamento , Pessoa de Meia-Idade , Neoplasias/diagnóstico , Neoplasias/mortalidade , Ontário , Análise de Regressão , População Rural/estatística & dados numéricos , Fatores de TempoRESUMO
BACKGROUND: Survivors of childhood cancer are at considerable risk of experiencing treatment-related adverse health outcomes. To provide survivors with specialized care focused on these risks during adulthood, the government of Ontario funded a provincial network of specialized survivor clinics in 1999. The aim of this study was to determine whether prior attendance at survivor clinics by adult survivors of childhood cancer was associated with rates of emergency department (ED) visits. METHODS: This was a population-based, retrospective cohort study using multiple linked administrative health databases. The cohort consisted of all adult survivors of childhood cancer diagnosed between January 1, 1986 and December 31, 2005 in Ontario, Canada. A recurrent event regression model was used to evaluate the association between prior attendance at survivor clinics and the rate of ED visits; adjustments were made for individual, demographic, treatment, and provider characteristics. RESULTS: The study consisted of 3912 adult survivors of childhood cancer. Individuals who had at least 1 prior visit to a survivor clinic had a 19% decreased rate of ED visits in comparison with individuals who had not visited a survivor clinic (adjusted relative rate, 0.81; 95% confidence interval, 0.78-0.85). Each additional prior visit to a survivor clinic was associated with a 5% decrease in the rate of ED visits (adjusted relative rate, 0.95; 95% confidence interval, 0.93-0.96). These results were independent of whether or not survivors received care from a primary care physician. CONCLUSIONS: Attendance at a specialized survivor clinic was significantly associated with decreased ED visits among adult survivors of childhood cancer.
Assuntos
Assistência Ambulatorial/organização & administração , Serviço Hospitalar de Emergência/estatística & dados numéricos , Neoplasias/terapia , Sobreviventes/estatística & dados numéricos , Adulto , Assistência Ambulatorial/métodos , Criança , Estudos de Coortes , Feminino , Humanos , Armazenamento e Recuperação da Informação , Masculino , Análise Multivariada , Ontário , Análise de Regressão , Estudos Retrospectivos , Fatores de RiscoRESUMO
OBJECTIVE: To determine whether visits to a primary care provider (PCP) are associated with the uptake of periodic mammograms as women get older. METHODS: The cohort consisted of 2,389,889 women resident in Ontario, Canada, aged 50 to 79 at any point from 2001 to 2010, who were cancer-free and eligible for the Ontario Health Insurance Plan prior to study entry. Non-parametric estimation was used to describe the mean cumulative number of periodic mammograms for women with and without recent exposure to a PCP, as a function of age. Using age as the time scale, a recurrent event regression model was also implemented to examine the association between exposure to a PCP and rate of periodic mammograms, adjusted for income quintile and comorbidity. RESULTS: The mean observation window was 7.0 years. Uptake of periodic mammograms was significantly higher for women with recent exposure to a PCP compared with those without. This trend remained consistent as women aged, and the magnitude of the association increased for women aged 65 or older. The relative rate of periodic mammograms was lower than 1 and consistently decreased as women from lower income quintiles were compared with women from the wealthiest quintile. CONCLUSION: Visits to a PCP play an important role in uptake of periodic mammograms, and this association increases as women age.