Socioeconomic Deprivation and Invasive Breast Cancer Incidence by Stage at Diagnosis: A Possible Explanation to the Breast Cancer Social Paradox.

In this study, we assessed the influence of area-based socioeconomic deprivation on the incidence of invasive breast cancer (BC) in France, according to stage at diagnosis. All women from six mainland French departments, aged 15+ years, and diagnosed with a primary invasive breast carcinoma between 2008 and 2015 were included (n = 33,298). Area-based socioeconomic deprivation was determined using the French version of the European Deprivation Index. Age-standardized incidence rates (ASIR) by socioeconomic deprivation and stage at diagnosis were compared estimating incidence rate ratios (IRRs) adjusted for age at diagnosis and rurality of residence. Compared to the most affluent areas, significantly lower IRRs were found in the most deprived areas for all-stages (0.85, 95% CI 0.81-0.89), stage I (0.77, 95% CI 0.72-0.82), and stage II (0.84, 95% CI 0.78-0.90). On the contrary, for stages III-IV, significantly higher IRRs (1.18, 95% CI 1.08-1.29) were found in the most deprived areas. These findings provide a possible explanation to similar or higher mortality rates, despite overall lower incidence rates, observed in women living in more deprived areas when compared to their affluent counterparts. Socioeconomic inequalities in access to healthcare services, including screening, could be plausible explanations for this phenomenon, underlying the need for further research.

Early prediction of the impact of public health policies on obesity and lifetime risk of type 2 diabetes: A modelling approach.

OBJECTIVE: Help public health decision-making requires a better understanding of the dynamics of obesity and type 2 diabetes and an assessement of different strategies to decrease their burdens. METHODS: Based on 97,848 individual data, collected in the French Health, Health Care and Insurance Survey over 1998-2014, a Markov model was developed to describe the progression of being overweight to obesity, and the onset of type 2 diabetes. This model traces and predicts 2022-2027 burdens of obesity and type 2 diabetes, and lifetime risk of diabetes, according to different scenarios aiming at minimum to stabilize obesity at 5 years. RESULTS: Estimated risks of type 2 diabetes increase from 0.09% (normal weight) to 1.56% (obesity II-III). Compared to the before 1995 period, progression risks are estimated to have nearly doubled for obesity and tripled for type 2 diabetes. Consequently, over 2022-2027, the prevalence of obesity and type 2 diabetes will continue to increase from 17.3% to 18.2% and from 7.3% to 8.1%, respectively. Scenarios statibilizing obesity would require a 22%-decrease in the probability of move up (scenario 1) or a 33%-increase in the probability of move down (scenario 2) one BMI class. However, this stabilization will not affect the increase of diabetes prevalence whereas lifetime risk of diabetes would decrease (30.9% to 27.0%). Combining both scenarios would decrease obesity by 9.9%. Only the prevalence of obesity III shows early change able to predict the outcome of a strategy: for example, 6.7%-decrease at one year, 13.3%-decrease at two years with scenario 1 stabilizing obesity at 5 years. CONCLUSIONS: Prevalences of obesity and type 2 diabetes will still increase over the next 5 years. Stabilizing obesity may decrease lifetime risks of type 2 diabetes without affecting its short-term prevalence. Our study highlights that, to early assess the effectiveness of their program, public health policy makers should rely on the change in prevalence of obesity III.

Socioeconomic and geographic disparities of breast cancer incidence according to stage at diagnosis in France.

PURPOSE: Low socioeconomic background (SB) has been associated with lower breast cancer (BC) incidence and higher BC mortality. One explanation of this paradox is the higher frequency of advanced BC observed in deprived women. However, it is still unclear if SB affects similarly BC incidence. This study investigated the link between SB and early/advanced BC incidence from Loire-Atlantique/Vendee Cancer registry data (France). MATERIALS AND METHODS: Fourteen thousand three hundred fifty three women living in the geographic area covered by the registry and diagnosed with a primary BC in 2008-2015 were included. SB was approached by a combination of two ecological indexes (French European Deprivation Index and urban/rural residence place). Mixed effects logistic and Poisson regressions were used, respectively, to estimate the odds of advanced (stage ≥ II) BC and the ratio of incidence rates of early (stage 0-I) and advanced BC according to SB, overall and by age group (< 50, 50-74, ≥ 75). RESULTS: Compared to women living in affluent-urban areas, women living in deprived-urban and deprived-rural areas had a higher proportion of advanced BC [respectively, OR = 1.11 (1.01-1.22), OR = 1.60 (1.25-2.06)] and lower overall (from - 6 to - 15%) and early (from - 9 to - 31%) BC incidences rates Advanced BC incidence rates were not influenced by SB. These patterns were similar in women under 75 years, especially in women living in deprived-rural areas. In the elderly, no association between SB and BC frequency/incidence rates by stage was found. CONCLUSION: Although advanced BC was more frequent in women living in deprived and rural areas, SB did not influence advanced BC incidence. Therefore, differences observed in overall BC incidence according to SB were only due to higher incidence of early BC in affluent and urban areas. Future research should confirm these results in other French areas.

Is survival rate lower after breast cancer in deprived women according to disease stage?

BACKGROUND: Socioeconomic deprivation has been associated with lower breast cancer (BC) survival, but the influence of stage at diagnosis on this association merits further study. Our aim was to investigate this association using the Loire-Atlantique/Vendee Cancer Registry (France). METHODS: Twelve-thousand seven-hundred thirty-eight women living in the area covered by the registry and diagnosed with invasive breast carcinoma between 2008 and 2015 were included in the study. They were censored at maximal 6 years. Deprivation was measured by the French European Deprivation Index. Excess hazard and net survival were estimated for deprivation level, stage and age at diagnosis using a flexible excess mortality hazard model. RESULTS: After adjustment by stage, women living in the most deprived areas had a borderline non-significant higher excess mortality hazard (+25% (95% CI: -3%; +62%)) compared to those living in the least deprived areas. Stage-adjusted 5-year net survival differed significantly between these two subgroups (respectively, 88.2% (95% CI:85.2%-90.5%) and 92.5% (95% CI:90.6%-93.9%)). CONCLUSION: BC survival remained lower in deprived areas in France, despite universal access to cancer care. Intensification of prevention measures could help to reduce advanced BC, responsible for the majority of deaths from BC. A better understanding of remaining social disparities is crucial to implement specific interventions.

Benefits of tailored hepatocellular carcinoma screening in patients with cirrhosis on cancer-specific and overall mortality: A modeling approach.

To validate cancer screening programs, experts recommend estimating effects on case fatality rates (CFRs) and cancer-specific mortality. This study evaluates hepatocellular carcinoma (HCC) screening in patients with cirrhosis for those outcomes using a modeling approach. We designed a Markov model to assess 10-year HCC-CFR, HCC-related, and overall mortality per 100,000 screened patients with compensated cirrhosis. The model evaluates different HCC surveillance intervals (none, annual [12 months], semiannual [6 months], or quarterly [3 months]) and imaging modalities (ultrasound [US] or magnetic resonance imaging [MRI]) in various annual incidences (0.2%, 0.4%, or 1.5%). Compared to no surveillance, 6-month US reduced the 10-year HCC-CFR from 77% to 46%. With annual incidences of 0.2%, 0.4%, and 1.5%, the model predicted 281, 565, and 2059 fewer HCC-related deaths, respectively, and 187, 374, and 1356 fewer total deaths per 100,000 screened patients, respectively. Combining alpha-fetoprotein screening to 6-month US led to 32, 63, and 230 fewer HCC-related deaths per 100,000 screened patients for annual incidences of 0.2%, 0.4%, and 1.5%, respectively. Compared to 6-month US, 3-month US reduced cancer-related mortality by 14%, predicting 61, 123, and 446 fewer HCC-related deaths per 100,000 screened patients with annual incidences of 0.2%, 0.4%, and 1.5%, respectively. Compared to 6-month US, 6-month MRI (-17%) and 12-month MRI (-6%) reduced HCC-related mortality. Compared to 6-month US, overall mortality reductions ranged from -0.1% to -1.3% when using 3-month US or MRI. A US surveillance interval of 6 months improves HCC-related and overall mortality compared to no surveillance. A shorter US interval or using MRI could reduce HCC-CFR and HCC-related mortality, with a modest effect on overall mortality.

Morbid obesity increases death and dropout from the liver transplantation waiting list: A prospective cohort study.

Liver transplant (LT) candidates with a body mass index (BMI) over 40 kg/m2 have lower access to a liver graft without clear explanation. Thus, we studied the impact of obesity on the waiting list (WL) and aimed to explore graft proposals and refusal. METHOD: Data between January 2007 and December 2017 were extracted from the French prospective national database: CRISTAL. Competing risk analyses were performed to evaluate predictors of receiving LT. Competitive events were (1) death/WL removal for disease aggravation or (2) improvement. The link between grade obesity, grafts propositions, and reason for refusal was studied. RESULTS: 15,184 patients were analysed: 10,813 transplant, 2847 death/dropout for aggravation, 748 redirected for improvement, and 776 censored. Mortality/dropout were higher in BMI over 35 (18% vs. 14% 1 year after listing) than in other candidates. In multivariate analysis, BMI>35, age, hepatic encephalopathy, and ascites were independent predictors of death/dropout. Candidates with a BMI ≥ 35 kg/m2 had reduced access to LT, without differences in graft proposals. However, grafts refusal was more frequent especially for 'morphological incompatibility' (14.9% vs. 12.7% p < 0.01). CONCLUSION: BMI over 35 kg/m2 reduces access to LT with increased risk of dropout and mortality. Increased mortality and dropout could be due to a lower access to liver graft secondary to increased graft refusal for morphological incompatibility.

A tool to predict progression of non-alcoholic fatty liver disease in severely obese patients.

BACKGROUND & AIMS: Severely obese patients are a growing population at risk of non-alcoholic fatty liver disease (NAFLD). Considering the increasing burden, a predictive tool of NAFLD progression would be of interest. Our objective was to provide a tool allowing general practitioners to identify and refer the patients most at risk, and specialists to estimate disease progression and adapt the therapeutic strategy. METHODS: This predictive tool is based on a Markov model simulating steatosis, fibrosis and non-alcoholic steatohepatitis (NASH) evolution. This model was developped from data of 1801 severely obese, bariatric surgery candidates, with histological assessment, integrating duration of exposure to risk factors. It is then able to predict current disease severity in the absence of assessment, and future cirrhosis risk based on current stage. RESULTS: The model quantifies the impact of sex, body-mass index at 20, diabetes, age of overweight onset, on progression. For example, for 40-year-old severely obese patients seen by the general practitioners: (a) non-diabetic woman overweight at 20, and (b) diabetic man overweight at 10, without disease assessment, the model predicts their current risk to have NASH or F3-F4: for (a) 5.7% and 0.6%, for (b) 16.1% and 10.0% respectively. If those patients have been diagnosed F2 by the specialist, the model predicts the 5-year cirrhosis risk: 1.8% in the absence of NASH and 6.0% in its presence for (a), 10.3% and 26.7% respectively, for (b). CONCLUSIONS: This model provides a decision-making tool to predict the risk of liver disease that could help manage severely obese patients.

A Model to Identify Heavy Drinkers at High Risk for Liver Disease Progression.

BACKGROUND & AIMS: Alcohol-related liver disease (ALD) causes chronic liver disease. We investigated how information on patients' drinking history and amount, stage of liver disease, and demographic feature can be used to determine risk of disease progression. METHODS: We collected data from 2334 heavy drinkers (50 g/day or more) with persistently abnormal results from liver tests who had been admitted to a hepato-gastroenterology unit in France from January 1982 through December 1997; patients with a recorded duration of alcohol abuse were assigned to the development cohort (n=1599; 75% men) or the validation cohort (n=735; 75% men), based on presence of a liver biopsy. We collected data from both cohorts on patient history and disease stage at the time of hospitalization. For the development cohort, severity of the disease was scored by the METAVIR (due to the availability of liver histology reports); in the validation cohort only the presence of liver complications was assessed. We developed a model of ALD progression and occurrence of liver complications (hepatocellular carcinoma and/or liver decompensation) in association with exposure to alcohol, age at the onset of heavy drinking, amount of alcohol intake, sex and body mass index. The model was fitted to the development cohort and then evaluated in the validation cohort. We then tested the ability of the model to predict disease progression for any patient profile (baseline evaluation). Patients with a 5-y weighted risk of liver complications greater than 5% were considered at high risk for disease progression. RESULTS: Model results are given for the following patient profiles: men and women, 40 y old, who started drinking at an age of 25 y, drank 150 g/day, and had a body mass index of 22 kg/m2 according to the disease severity at baseline evaluation. For men with baseline F0-F2 fibrosis, the model estimated the probabilities of normal liver, steatosis, or steatohepatitis at baseline to be 31.8%, 61.5% and 6.7%, respectively. The 5-y weighted risk of liver complications was 1.9%, ranging from 0.2% for men with normal liver at baseline evaluation to 10.3% for patients with steatohepatitis at baseline. For women with baseline F0-F2 fibrosis, probabilities of normal liver, steatosis, or steatohepatitis at baseline were 25.1%, 66.5% and 8.4%, respectively; the 5-y weighted risk of liver complications was 3.2%, ranging from 0.5% for women with normal liver at baseline to 14.7% for patients with steatohepatitis at baseline. Based on the model, men with F3-F4 fibrosis at baseline have a 24.5% 5-y weighted risk of complications (ranging from 20.2% to 34.5%) and women have a 30.1% 5-y weighted risk of complications (ranging from 24.7% to 41.0%). CONCLUSIONS: We developed a Markov model that integrates data on level and duration of alcohol use to identify patients at high risk of liver disease progression. This model might be used to adapt patient care pathways.