Registre des cancers de lIsere

Saint-Dié-des-Vosges, France

Registre des cancers de lIsere

Saint-Dié-des-Vosges, France
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Molinie F.,Registre des Cancers de Loire Atlantique Vendee | Vanier A.,University Pierre and Marie Curie | Vanier A.,Hopitaux Universitaires Pitie Salpetriere Charles Foix | Vanier A.,University of Nantes | And 9 more authors.
Breast Cancer Research and Treatment | Year: 2014

The objective of this work was to detail the incidence and mortality trends of invasive and in situ breast cancer (BC) in France, especially regarding the development of screening, over the 1990-2008 period. Data issued from nine population-based cancer registries were studied. The incidence of invasive BC increased annually by 0.8 % from 1990 to 1996 and more markedly by 3.2 % from 1996 to 2003, and then sharply decreased until 2006 (-2.3 % per year), especially among women aged 50-69 years (-4.9 % per year). This trend was similar whatever the introduction date of the organized screening (OS) program in the different areas. The incidence of ductal carcinoma in situ steadily increased between 1990 and 2005, particularly among women aged 50-69 years and 70 and older. At the same time, the mortality from BC decreased annually by 1.1 % over the entire study period. This decrease was more pronounced in women aged 40-49 and 50-69 and, during the 1990-1999 period, in the areas where OS began in 1989-1991. The similarity in the incidence trends for all periods of implementation of OS in the different areas was striking. This suggests that OS alone does not explain the changes observed in incidence rate. Our study highlights the importance of closely monitoring the changes in incidence and mortality indicators, and of better understanding the factors causing variation. © 2014 Springer Science+Business Media.


Delpierre C.,French Institute of Health and Medical Research | Delpierre C.,University Paul Sabatier | Lamy S.,French Institute of Health and Medical Research | Lamy S.,University Paul Sabatier | And 15 more authors.
Cancer Epidemiology | Year: 2013

Objective: To estimate the magnitude of over-diagnosis and of potential and actual over-treatment regarding prostate cancer, taking comorbidities into account. Materials and methods: We used a sample collected by the French cancer registries of 1840 cases (T1: 583; T2: 1257) diagnosed in 2001. The proportion of over-diagnosed and over-treated patients was estimated by comparing life expectancy (LE), including or not comorbidities, with natural LE with cancer, using several assumptions from the literature. We distinguished potential and actual over-treatment according to the treatment that patients actually received. Results: Among patients with T1 tumors the proportion of potential over-treatment using LE adjusted for comorbidity varied from 29.5% to 53.5%, using LE adjusted on comorbidities, and varied from 9.3% to 22.2% regarding actual over-treatment. Between 7.7% and 24.4% of patient's receiving a radical prostatectomy, and between 30.8% and 62.5% of those receiving radiotherapy, were over-treated. Among patients with T2 tumors, the proportions of potential and actual over-treatment were 0.9% and 2.0%. Two per cent of patients receiving a radical prostatectomy and 4.9% of those receiving radiotherapy were over-treated. Comorbidities dramatically increased these proportions to nearly 100% of patients, with more than two comorbidities being potentially over-treated and around 33% actually over-treated. Conclusions: According to the French incidence, 3200-4800 French patients may be over-treated, among whom a large proportion of patients had comorbidities. The real issue is to offer the most appropriate treatment to people with low-grade tumors and comorbidities. © 2013 Elsevier Ltd.


Tretarre B.,Registre des Tumeurs de lHerault | Molinie F.,Registre des Cancers de Loire Atlantique Vendee | Woronoff A.-S.,Registre des Tumeurs du Doubs et du Territoire de Belfort | Bossard N.,Service de Biostatistiques | And 13 more authors.
Gynecologic Oncology | Year: 2015

Objective The aim of this epidemiological study was to describe the incidence, mortality and survival of ovarian cancer (OC) in France, according to age, period of diagnosis, and histological type. Methods Incidence and mortality were estimated from 1980 to 2012 based on data in French cancer registries and from the Centre for Epidemiology of Causes of Death (CépiDc-Inserm) up to 2009. Net survival was estimated from registry data using the Pohar-Perme method, on cases diagnosed between 1989 and 2010, with date of last follow-up set at 30 June 2013. Results In 2012, 4615 cases of OC were diagnosed in France, and 3140 women died from OC. World population age-standardized incidence and mortality rates declined by respectively 0.6% and 1.2% per year between 1980 and 2012. Net survival at 5 years increased slightly, from 40% for the period 1989-1993 to 45% for the period 2005-2010. Net survival varied considerably according to histological type. Germ cell tumors had better net survival at 10 years (81%) compared to epithelial tumors (32%), sex cord-stromal tumors (40%) and tumors without biopsy (8%). Conclusions Our study shows a decline in incidence and mortality rates from ovarian cancer in France between 1980 and 2012, but net survival remains poor overall, and improved only slightly over the whole study period. © 2015 Elsevier Inc.


PubMed | Registre des cancers de la Somme, Registre des cancers de Lille et de sa zone de proximite, Registre des cancers de Loire Atlantique Vendee, Registre des cancers de lIsere and 11 more.
Type: Journal Article | Journal: Gynecologic oncology | Year: 2015

The aim of this epidemiological study was to describe the incidence, mortality and survival of ovarian cancer (OC) in France, according to age, period of diagnosis, and histological type.Incidence and mortality were estimated from 1980 to 2012 based on data in French cancer registries and from the Centre for Epidemiology of Causes of Death (CpiDc-Inserm) up to 2009. Net survival was estimated from registry data using the Pohar-Perme method, on cases diagnosed between 1989 and 2010, with date of last follow-up set at 30 June 2013.In 2012, 4615 cases of OC were diagnosed in France, and 3140 women died from OC. World population age-standardized incidence and mortality rates declined by respectively 0.6% and 1.2% per year between 1980 and 2012. Net survival at 5years increased slightly, from 40% for the period 1989-1993 to 45% for the period 2005-2010. Net survival varied considerably according to histological type. Germ cell tumors had better net survival at 10years (81%) compared to epithelial tumors (32%), sex cord-stromal tumors (40%) and tumors without biopsy (8%).Our study shows a decline in incidence and mortality rates from ovarian cancer in France between 1980 and 2012, but net survival remains poor overall, and improved only slightly over the whole study period.


Uhry Z.,Institute of Veille Sanitaire | Hedelin G.,University of Strasbourg | Colonna M.,Registre des Cancers de lIsere | Asselain B.,University Pierre and Marie Curie | And 9 more authors.
Statistical Methods in Medical Research | Year: 2010

This work presents a brief overview of Markov models in cancer screening evaluation and focuses on two specific models. A three-state model was first proposed to estimate jointly the sensitivity of the screening procedure and the average duration in the preclinical phase, i.e. the period when the cancer is asymptomatic but detectable by screening. A five-state model, incorporating lymph node involvement as a prognostic factor, was later proposed combined with a survival analysis to predict the mortality reduction associated with screening. The strengths and limitations of these two models are illustrated using data from French breast cancer service screening programmes. The three-state model is a useful frame but parameter estimates should be interpreted with caution. They are highly correlated and depend heavily on the parametric assumptions of the model. Our results pointed out a serious limitation to the five-state model, due to implicit assumptions which are not always verified. Although it may still be useful, there is a need for more flexible models. Over-diagnosis is an important issue for both models and induces bias in parameter estimates. It can be addressed by adding a non-progressive state, but this may provide an uncertain estimation of over-diagnosis. When the primary goal is to avoid bias, rather than to estimate over-diagnosis, it may be more appropriate to correct for over-diagnosis assuming different levels in a sensitivity analysis. This would be particularly relevant in a perspective of mortality reduction estimation. © The Author(s), 2010.


Colonna M.,Registre des Cancers de lIsere | Mitton N.,Registre des Cancers de lIsere | Schott A.-M.,Hospices Civils de Lyon | Schott A.-M.,University of Lyon | And 17 more authors.
Cancer Epidemiology | Year: 2012

Background Estimate complete, limited-duration, and hospital prevalence of breast cancer in a French Département covered by a population-based cancer registry and in whole France using complementary information sources. Methods: Incidence data from a cancer registry, national incidence estimations for France, mortality data, and hospital medico-administrative data were used to estimate the three prevalence indices. The methods included a modelling of epidemiological data and a specific process of data extraction from medico-administrative databases. Results: Limited-duration prevalence at 33 years was a proxy for complete prevalence only in patients aged less than 70 years. In 2007 and in women older than 15 years, the limited-duration prevalence at 33 years rate per 100,000 women was estimated at 2372 for Département Isère and 2354 for whole France. The latter rate corresponded to 613,000 women. The highest rate corresponded to women aged 65-74 years (6161 per 100,000 in whole France). About one third of the 33-year limited-duration prevalence cases were diagnosed five years before and about one fourth were hospitalized for breast-cancer-related care (i.e., hospital prevalence). In 2007, the rate of hospitalized women was 557 per 100,000 in whole France. Among the 120,310 women hospitalized for breast-cancer-related care in 2007, about 13% were diagnosed before 2004. Conclusion: Limited-duration prevalence (long- and short-term), and hospital prevalence are complementary indices of cancer prevalence. Their efficient direct or indirect estimations are essential to reflect the burden of the disease and forecast median- and long-term medical, economic, and social patient needs, especially after the initial treatment. © 2011 Elsevier Ltd.


Paviot B.T.,Jean Monnet University | Gomez F.,Center Leon Berard | Olive F.,Grenoble University Hospital Center | Polazzi S.,University of Lyon | And 8 more authors.
Methods of Information in Medicine | Year: 2011

Objectives: Little is known about cancer prevalence due to a lack of systematic recording of cancer patient follow-up data. To estimate the annual hospital prevalence of breast cancer in the general population of the Isère department (1.1 million inhabitants) in the Rhône-Alpes region, the second largest region in France (6 million inhabitants), we used the inpatient case-mix data, available in most European countries, to develop a method of cancer case identification. Methods: A selection process was applied to the acute care hospital datasets among women aged 18 years or older, living in the Isère department and treated for breast cancer between 2004 and 2007. The first step in case selection was based on the national anonymous unique patient identifier. The second step consisted of retrieving all hospital stays for each case. The third step was designed to detect inconsistencies in the coding of the primary localization. An algorithm based on ICD-10 code for the hospital admission diagnosis was used to rule out hospitali - zations unrelated to breast cancer. Five possible models for estimating prevalence were created combining selection steps with the admission diagnosis algorithm. Results: Hospital prevalence over the fouryear period varied from 6073 breast cancer cases for the simplest model (first selection step without the admission diagnosis algorithm) to 4951 when the first selection step was associated with the breast cancer code as admission diagnosis. The model combining the third selection step with a breast cancerspecific admission reason provided 5275 prevalent cases. Conclusion: The last model seems more appropriate for case-mix-data coding. Selecting admission diagnosis improved specificity. Combining all hospital stays for each patient has improved diagnostic sensitivity. © Schattauer 2011.


Uhry Z.,Institute of Veille Sanitaire | Hedelin G.,University of Strasbourg | Colonna M.,Registre des cancers de lIsere | Asselain B.,University Pierre and Marie Curie | And 13 more authors.
Cancer Epidemiology | Year: 2011

Introduction: This study aimed at modelling the effect of organized breast cancer screening on mortality in France. It combined results from a Markov model for breast cancer progression, to predict number of cases by node status, and from relative survival analyses, to predict deaths. The method estimated the relative risk of mortality at 8 years, in women aged 50-69, between a population screened every two years and a reference population. Methods: Analyses concerned cases diagnosed between 1990 and 1996, with a follow-up up to 2004 for the vital status. Markov models analysed data from 3 screening programs (300,000 mammographies) and took into account opportunistic screening among participants to avoid bias in parameter's estimates. We used survival data from cancers in the general population (n = 918, 7 cancer registries) and from screened cancers (n = 565, 3 cancer registries), after excluding a subgroup of screened cases with a particularly high survival. Sensitivity analyses were performed. Results: Markov model main analysis lacked of fit in two out of three districts. Fit was improved in stratified analyses by age or district, though some lack of fit persisted in two districts. Assuming 10% or 20% overdiagnosed screened cancers, mortality reduction was estimated as 23% (95% CI: 4, 38%) and 19% (CI: -3, 35%) respectively. Results were highly sensitive to the exclusion in the screened cancers survival analysis. Conversely, RR estimates varied moderately according to the Markov model parameters used (stratified by age or district). Conclusion: The study aimed at estimating the effect of screening in a screened population compared to an unscreened control group. Such a control group does not exist in France, and we used a general population contaminated by opportunistic screening to provide a conservative estimate. Conservative choices were systematically adopted to avoid favourable estimates. A selection bias might however affect the estimates, though it should be moderate because extreme social classes are under-represented among participants. This modelling provided broad estimates for the effect of organized biennial screening in France in the early nineteen-nineties. Results will be strengthened with longer follow-up. © 2010 Elsevier Ltd.


Molinie F.,Registre des cancers de Loire Atlantique Vendee | Leux C.,Registre des cancers de Loire Atlantique Vendee | Delafosse P.,Registre des cancers de lIsere | Ayrault-Piault S.,Registre des cancers de Loire Atlantique Vendee | And 8 more authors.
Breast | Year: 2013

Waiting times are key indicators of a health's system performance, but are not routinely available in France. We studied waiting times for diagnosis and treatment according to patients' characteristics, tumours' characteristics and medical management options in a sample of 1494 breast cancers recorded in population-based registries. The median waiting time from the first imaging detection to the treatment initiation was 34 days. Older age, co-morbidity, smaller size of tumour, detection by organised screening, biopsy, increasing number of specimens removed, multidisciplinary consulting meetings and surgery as initial treatment were related to increased waiting times in multivariate models. Many of these factors were related to good practices guidelines. However, the strong influence of organised screening programme and the disparity of waiting times according to geographical areas were of concern. Better scheduling of diagnostic tests and treatment propositions should improve waiting times in the management of breast cancer in France. © 2013 Elsevier Ltd.


PubMed | Registre des Cancers de lIsere
Type: Journal Article | Journal: Cancer epidemiology | Year: 2012

Estimate complete, limited-duration, and hospital prevalence of breast cancer in a French Dpartement covered by a population-based cancer registry and in whole France using complementary information sources.Incidence data from a cancer registry, national incidence estimations for France, mortality data, and hospital medico-administrative data were used to estimate the three prevalence indices. The methods included a modelling of epidemiological data and a specific process of data extraction from medico-administrative databases.Limited-duration prevalence at 33 years was a proxy for complete prevalence only in patients aged less than 70 years. In 2007 and in women older than 15 years, the limited-duration prevalence at 33 years rate per 100,000 women was estimated at 2372 for Dpartement Isre and 2354 for whole France. The latter rate corresponded to 613,000 women. The highest rate corresponded to women aged 65-74 years (6161 per 100,000 in whole France). About one third of the 33-year limited-duration prevalence cases were diagnosed five years before and about one fourth were hospitalized for breast-cancer-related care (i.e., hospital prevalence). In 2007, the rate of hospitalized women was 557 per 100,000 in whole France. Among the 120,310 women hospitalized for breast-cancer-related care in 2007, about 13% were diagnosed before 2004.Limited-duration prevalence (long- and short-term), and hospital prevalence are complementary indices of cancer prevalence. Their efficient direct or indirect estimations are essential to reflect the burden of the disease and forecast median- and long-term medical, economic, and social patient needs, especially after the initial treatment.

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