Incidence trends for potentially human papillomavirus-related and -unrelated head and neck cancers in France using population-based cancer registries data: 1980-2012.

Human papillomavirus (HPV) has been recently recognised as a carcinogenic factor for a subset of head and neck cancers (HNC). In Europe, France has one of the highest incidence rates of HNC. The aim of this study is to explore changes in HNC incidence in France, potentially in relation with infection by HPV. HNC were classified into two anatomical groups: potentially HPV-related and HPV-unrelated. Trends over the period 1980-2012 were analysed by an age-period-cohort model based on data from eleven French cancer registries. Among men, the age-standardised incidence rate (ASR) of HNC decreased in both groups, but less so for HPV-related sites as compared to unrelated sites, especially in recent years (annual percentage change [APC] over the period 2005-2012: -3.5% vs. -5.4%). Among women, the ASR increased in both groups, but more rapidly for HPV-related as compared to unrelated sites (APC over the period 2005-2012: +1.9% vs. -0.4%). This preferential growth of HPV-related versus unrelated HNC was observed in the cohorts born from 1930 to 1935. The differences in trends between possible HPV-related and HPV-unrelated sites suggest an increasing incidence of HNC due to HPV infection. The difference was less marked in men as compared to women, most likely because of a higher contamination in the HPV-related group by cancers due to tobacco or alcohol consumption. The pattern observed is consistent with observations made in other countries, with studies of HPV prevalence in HNC and the evolution of sexual behaviour in France

Describing the association between socioeconomic inequalities and cancer survival: methodological guidelines and illustration with population-based data.

BACKGROUND: Describing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. We propose guidelines for addressing these challenges and illustrate their implementation on French population-based data. METHODS: We analyzed 17 cancers. Socioeconomic deprivation was measured by an ecological measure, the European Deprivation Index (EDI). The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. The model included a cluster-specific random effect to deal with the hierarchical structure of the data. RESULTS: We reported the conventional age-standardized net survival (ASNS) and described the changes of the EMH over the time since diagnosis at different levels of deprivation. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. The median excess hazard ratio quantified the general contextual effect. Lip-oral cavity-pharynx cancer in men showed the widest deprivation gap, with 5-year ASNS at 41% and 29% for deprivation quintiles 1 and 5, respectively, and we found a nonlinear association between the EDI and the EMH. The EDI accounted for a substantial part of the general contextual effect on the EMH. The association between the EDI and the EMH was time dependent in stomach and pancreas cancers in men and in cervix cancer. CONCLUSION: The methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems

Flexible and structured survival model for a simultaneous estimation of non-linear and non-proportional effects and complex interactions between continuous variables: Performance of this multidimensional penalized spline approach in net survival trend analysis.

Cancer survival trend analyses are essential to describe accurately the way medical practices impact patients' survival according to the year of diagnosis. To this end, survival models should be able to account simultaneously for non-linear and non-proportional effects and for complex interactions between continuous variables. However, in the statistical literature, there is no consensus yet on how to build such models that should be flexible but still provide smooth estimates of survival. In this article, we tackle this challenge by smoothing the complex hypersurface (time since diagnosis, age at diagnosis, year of diagnosis, and mortality hazard) using a multidimensional penalized spline built from the tensor product of the marginal bases of time, age, and year. Considering this penalized survival model as a Poisson model, we assess the performance of this approach in estimating the net survival with a comprehensive simulation study that reflects simple and complex realistic survival trends. The bias was generally small and the root mean squared error was good and often similar to that of the true model that generated the data. This parametric approach offers many advantages and interesting prospects (such as forecasting) that make it an attractive and efficient tool for survival trend analyses

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Pronostic du cancer du sein chez les femmes jeunes (étude à partir de données d'un registre des cancers)

LYON1-BU Santé (693882101) / SudocSudocFranceF

Estimation de la probabilité brute de décès lié au cancer (application à des données de registres (réseau Francim))

LYON1-BU Santé (693882101) / SudocSudocFranceF

Réflexions sur l'optimisation de quelque méthodes statistiques en épidémiologie du cancer du sein

La modélisation de l'effet de variables continues et éventuellement dépendantes du temps dans l'incidence et le pronostic du cancer du sein présente quelques particularités méthodologiques que nous avons approfondies à partir de deux exemples. Le premier exemple porte sur la prise en compte de l'âge à la ménopause dans les études d'incidence. Nous avons utilisé un modèle d'incidence dont les paramètres ont été estimés en prenant en compte la variabilité inter-individuelle des facteurs génitaux intervenant dans le modèle. Ceci a rendu possible une étude de simulation dont l'objectif était d'étudier différentes modélisations de la covariable " ménopause ". Le deuxième exemple porte sur l'étude de la forme fonctionnelle reliant un marqueur tumoral quantitatif à son impact pronostique, à l'aide des splines de lissage (Smoothing Splines) et de la méthode des polynômes à puissance fractionnaire (Fractional Polynomials).LYON1-BU.Sciences (692662101) / SudocSudocFranceF

Hazard regression model and cure rate model in colon cancer relative survival trends: are they telling the same story?

Hazard regression models and cure rate models can be advantageously used in cancer relative survival analysis. We explored the advantages and limits of these two models in colon cancer and focused on the prognostic impact of the year of diagnosis on survival according to the TNM stage at diagnosis. The analysis concerned 9,998 patients from three French registries. In the hazard regression model, the baseline excess death hazard and the time-dependent effects of covariates were modelled using regression splines. The cure rate model estimated the proportion of 'cured' patients and the excess death hazard in 'non-cured' patients. The effects of year of diagnosis on these parameters were estimated for each TNM cancer stage. With the hazard regression model, the excess death hazard decreased significantly with more recent years of diagnoses (hazard ratio, HR 0.97 in stage III and 0.98 in stage IV, P 0.5). The two models were complementary and concordant in estimating colon cancer survival and the effects of covariates. They provided two different points of view of the same phenomenon: recent years of diagnosis had a favourable effect on survival, but not on cure

Total and partial cancer prevalence in the adult French population in 2008.

BACKGROUND: To provide estimations of partial and total prevalence of 24 cancer sites in France in 2008. The estimations of partial prevalence were compared with the previous estimations for 2002. METHODS: Nationwide estimations of incidence and survival data from cancer registries were used for partial prevalence. Nationwide incidence and mortality data were used to estimate total prevalence. RESULTS: At the end of 2008, in France, nearly 3 million people still alive had received a diagnosis of cancer. Of all prevalent cases, 36% were diagnosed 0 to 5 years earlier and 43% diagnosed 6 to 10 years earlier. The cancer sites with the highest prevalence were the prostate, the breast, and the colon-rectum. The changes in partial prevalence over 5 years (2002 to 2008) were considerable (+244,000 cases) and deemed to be highly related to changes in incidence. CONCLUSION: The present estimations update the French prevalence data and highlight the burden of cancer in the population, especially in the elderly. The methods of this study had the advantage of using recent incidence and survival data, which is necessary to show sudden changes in incidence trends and changes in survival that impact prevalence