Jordi Blanch

Tumor phenotype and breast density in distinct categories of interval cancer: results of population-based mammography screening in Spain

IntroductionInterval cancers are tumors arising after a negative screening episode and before the next screening invitation. They can be classified into true interval cancers, false-negatives, minimal-sign cancers, and occult tumors based on mammographic findings in screening and diagnostic mammograms. This study aimed to describe tumor-related characteristics and the association of breast density and tumor phenotype within four interval cancer categories.MethodsWe included 2,245 invasive tumors (1,297 screening-detected and 948 interval cancers) diagnosed from 2000 to 2009 among 645,764 women aged 45 to 69 who underwent biennial screening in Spain. Interval cancers were classified by a semi-informed retrospective review into true interval cancers (n = 455), false-negatives (n = 224), minimal-sign (n = 166), and occult tumors (n = 103). Breast density was evaluated using Boyd’s scale and was conflated into: <25%; 25 to 50%; 50 to 75%; >75%. Tumor-related information was obtained from cancer registries and clinical records. Tumor phenotype was defined as follows: luminal A: ER+/HER2- or PR+/HER2-; luminal B: ER+/HER2+ or PR+/HER2+; HER2: ER-/PR-/HER2+; triple-negative: ER-/PR-/HER2-. The association of tumor phenotype and breast density was assessed using a multinomial logistic regression model. Adjusted odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. All statistical tests were two-sided.ResultsForty-eight percent of interval cancers were true interval cancers and 23.6% false-negatives. True interval cancers were associated with HER2 and triple-negative phenotypes (OR = 1.91 (95% CI:1.22-2.96), OR = 2.07 (95% CI:1.42-3.01), respectively) and extremely dense breasts (>75%) (OR = 1.67 (95% CI:1.08-2.56)). However, among true interval cancers a higher proportion of triple-negative tumors was observed in predominantly fatty breasts (<25%) than in denser breasts (28.7%, 21.4%, 11.3% and 14.3%, respectively; <0.001). False-negatives and occult tumors had similar phenotypic characteristics to screening-detected cancers, extreme breast density being strongly associated with occult tumors (OR = 6.23 (95% CI:2.65-14.66)). Minimal-sign cancers were biologically close to true interval cancers but showed no association with breast density.ConclusionsOur findings revealed that both the distribution of tumor phenotype and breast density play specific and independent roles in each category of interval cancer. Further research is needed to understand the biological basis of the overrepresentation of triple-negative phenotype among predominantly fatty breasts in true interval cancers.

Aggressiveness features and outcomes of true interval cancers: comparison between screen-detected and symptom-detected cancers.

The question of whether screen detection confers an additional survival benefit in breast cancer is unclear and subject to several biases. Our aim was to examine the role of the diagnostic method (screen-detected, symptom-detected, and true interval cancers) and the clinical–pathological features in relapse-free survival and overall survival in breast cancer patients. We included 228 invasive breast cancers diagnosed in Barcelona from 1996 to 2008 among women aged 50–69 years. Ninety-seven patients were screen detected within the screening, 34 truly arose between 2-year screening mammograms (true interval cancers), and 97 were symptom detected outside the screening. The clinical–pathological features at diagnosis were compared. The overall and disease-free survival probabilities were computed using the Kaplan–Meier method. Cox proportional hazard models were applied, with adjustment by clinical–pathological variables. At diagnosis, symptom-detected and true interval cancers were in more advanced stages and were less differentiated. The highest proportion of triple-negative cancers was detected among true interval cancers (P=0.002). At 5 years of follow-up, the disease-free survival rates for screen-detected, true interval, and symptom-detected cancers were 87.5% (95% confidence interval, 80.5–95.2%), 64.1% (46.4–88.5%), and 79.4% (71.0–88.8%), respectively, and the overall survival rates were 94.5% (89.3–99.9%), 65.5% (47.1–91.2%), and 85.6% (78.3–93.6%), respectively. True interval cancers had the highest hazard ratio for relapse prediction (1.89; 0.67–5.31) and a hazard ratio of death of 5.55 (1.61–19.15) after adjustment for tumor–node–metastasis stage and phenotype. Clinically detected tumors, especially true interval cancers, more frequently showed biological features related to worse prognosis and were associated with poorer survival even after adjustment for clinical–pathological characteristics.

Breast cancer detection risk in screening mammography after a false-positive result

BACKGROUND False-positives are a major concern in breast cancer screening. However, false-positives have been little evaluated as a prognostic factor for cancer detection. Our aim was to evaluate the association of false-positive results with the cancer detection risk in subsequent screening participations over a 17-year period. METHODS This is a retrospective cohort study of 762,506 women aged 45-69 years, with at least two screening participations, who underwent 2,594,146 screening mammograms from 1990 to 2006. Multilevel discrete-time hazard models were used to estimate the adjusted odds ratios (OR) of breast cancer detection in subsequent screening participations in women with false-positive results. RESULTS False-positives involving a fine-needle aspiration cytology or a biopsy had a higher cancer detection risk than those involving additional imaging procedures alone (OR = 2.69; 95%CI: 2.28-3.16 and OR = 1.81; 95%CI: 1.70-1.94, respectively). The risk of cancer detection increased substantially if women with cytology or biopsy had a familial history of breast cancer (OR = 4.64; 95%CI: 3.23-6.66). Other factors associated with an increased cancer detection risk were age 65-69 years (OR = 1.84; 95%CI: 1.67-2.03), non-attendance at the previous screening invitation (OR = 1.26; 95%CI: 1.11-1.43), and having undergone a previous benign biopsy outside the screening program (OR = 1.24; 95%CI: 1.13-1.35). CONCLUSION Women with a false-positive test have an increased risk of cancer detection in subsequent screening participations, especially those with a false-positive result involving cytology or biopsy. Understanding the factors behind this association could provide valuable information to increase the effectiveness of breast cancer screening.

Patterns of statin use and cholesterol goal attainment in a high-risk cardiovascular population: A retrospective study of primary care electronic medical records

OBJECTIVE To describe real-life patterns of statin use and cholesterol goal attainment in a retrospective cohort of patients with high cardiovascular risk. METHODS Retrospective cohort study of 21,636 individuals, 18.34% women, mean age 63.30 years (standard deviation 6.29). New statin users aged 35 to 74 years at high cardiovascular risk and with no previous cardiovascular disease in primary care electronic medical records (2006-2011). Patterns of statin use were based on statin type, potency, and 1-year statin switches. OUTCOMES Relative mean reductions over 1 year and probability of goal attainment (<3.3 mmol/L). Natural patterns of statin use were identified using multiple correspondence analysis; general linear and logistic models were used to estimate low-density lipoprotein cholesterol (LDL-C) reductions and goal attainment probability. RESULTS Three patterns of statin use were defined: low (3.82% of the population), moderate (71.94%), and high intensity (24.24%). After 1 year, potency decreased 42.74%, 64.16%, and 50.94%, respectively, and 37.41%, 29.47%, and 30.16% of the population stopped taking statins in low, moderate, and high patterns, respectively. Relative reductions in LDL-C: low intensity, 15.7% (95% confidence interval [CI]: -22.96 to 54.36); moderate intensity, 29.72% (95% CI: 29.12-30.32); and high intensity, 24.20% (95% CI: -8.08 to 40.32). There was a direct relationship between higher intensity patterns and greater probability of goal attainment. CONCLUSIONS Three real-life patterns of statin use were identified. Lipid management strategies in primary care should focus on improving adherence to treatment. People starting at low potency should switch to a moderate pattern; more intensive therapies should be considered in who require a larger LDL-C reduction to reach therapeutic targets, patients with good treatment adherence who do not achieve the goal with a moderate pattern of therapy or patients at very high risk.

Linking of primary care records to census data to study the association between socioeconomic status and cancer incidence in Southern Europe: a nation-wide ecological study.

Background Area-based measures of economic deprivation are seldom applied to large medical records databases to establish population-scale associations between deprivation and disease. Objective To study the association between deprivation and incidence of common cancer types in a Southern European region. Methods Retrospective ecological study using the SIDIAP (Information System for the Development of Research in Primary Care) database of longitudinal electronic medical records for a representative population of Catalonia (Spain) and the MEDEA index based on urban socioeconomic indicators in the Spanish census. Study outcomes were incident cervical, breast, colorectal, prostate, and lung cancer in 2009–2012. The completeness of SIDIAP cancer recording was evaluated through linkage of a geographic data subset to a hospital cancer registry. Associations between MEDEA quintiles and cancer incidence was evaluated using zero-inflated Poisson regression adjusted for sex, age, smoking, alcoholism, obesity, hypertension, and diabetes. Results SIDIAP sensitivity was 63% to 92% for the five cancers studied. There was direct association between deprivation and lung, colorectal, and cervical cancer: incidence rate ratios (IRR) 1.82 [1.64–2.01], IRR 1.60 [1.34–1.90], IRR 1.22 [1.07–1.38], respectively, comparing the most deprived to most affluent areas. In wealthy areas, prostate and breast cancers were more common: IRR 0.92 [0.80–1.00], IRR 0.91 [0.78–1.06]. Adjustment for confounders attenuated the association with lung cancer risk (fully adjusted IRR 1.16 [1.08–1.25]), reversed the direction of the association with colorectal cancer (IRR 0.90 [0.84–0.95]), and did not modify the associations with cervical (IRR 1.27 [1.11–1.45]), prostate (0.74 [0.69–0.80]), and breast (0.76 [0.71–0.81]) cancer. Conclusions Deprivation is associated differently with the occurrence of various cancer types. These results provide evidence that MEDEA is a useful, area-based deprivation index for analyses of the SIDIAP database. This information will be useful to improve screening programs, cancer prevention and management strategies, to reach patients more effectively, particularly in deprived urban areas.

Impact of Risk Factors on Different Interval Cancer Subtypes in a Population-Based Breast Cancer Screening Programme

Background Interval cancers are primary breast cancers diagnosed in women after a negative screening test and before the next screening invitation. Our aim was to evaluate risk factors for interval cancer and their subtypes and to compare the risk factors identified with those associated with incident screen-detected cancers. Methods We analyzed data from 645,764 women participating in the Spanish breast cancer screening program from 2000–2006 and followed-up until 2009. A total of 5,309 screen-detected and 1,653 interval cancers were diagnosed. Among the latter, 1,012 could be classified on the basis of findings in screening and diagnostic mammograms, consisting of 489 true interval cancers (48.2%), 235 false-negatives (23.2%), 172 minimal-signs (17.2%) and 114 occult tumors (11.3%). Information on the screening protocol and womens characteristics were obtained from the screening program registry. Cause-specific Cox regression models were used to estimate the hazard ratios (HR) of risks factors for interval cancer and incident screen-detected cancer. A multinomial regression model, using screen-detected tumors as a reference group, was used to assess the effect of breast density and other factors on the occurrence of interval cancer subtypes. Results A previous false-positive was the main risk factor for interval cancer (HR = 2.71, 95%CI: 2.28–3.23); this risk was higher for false-negatives (HR = 8.79, 95%CI: 6.24–12.40) than for true interval cancer (HR = 2.26, 95%CI: 1.59–3.21). A family history of breast cancer was associated with true intervals (HR = 2.11, 95%CI: 1.60–2.78), previous benign biopsy with a false-negatives (HR = 1.83, 95%CI: 1.23–2.71). High breast density was mainly associated with occult tumors (RRR = 4.92, 95%CI: 2.58–9.38), followed by true intervals (RRR = 1.67, 95%CI: 1.18–2.36) and false-negatives (RRR = 1.58, 95%CI: 1.00–2.49). Conclusion The role of womens characteristics differs among interval cancer subtypes. This information could be useful to improve effectiveness of breast cancer screening programmes and to better classify subgroups of women with different risks of developing cancer.

Statins for primary prevention of cardiovascular events and mortality in old and very old adults with and without type 2 diabetes: retrospective cohort study

Abstract Objective To assess whether statin treatment is associated with a reduction in atherosclerotic cardiovascular disease (CVD) and mortality in old and very old adults with and without diabetes. Design Retrospective cohort study. Setting Database of the Catalan primary care system (SIDIAP), Spain, 2006-15. Participants 46 864 people aged 75 years or more without clinically recognised atherosclerotic CVD. Participants were stratified by presence of type 2 diabetes mellitus and as statin non-users or new users. Main outcome measures Incidences of atherosclerotic CVD and all cause mortality compared using Cox proportional hazards modelling, adjusted by the propensity score of statin treatment. The relation of age with the effect of statins was assessed using both a categorical approach, stratifying the analysis by old (75-84 years) and very old (≥85 years) age groups, and a continuous analysis, using an additive Cox proportional hazard model. Results The cohort included 46 864 participants (mean age 77 years; 63% women; median follow-up 5.6 years). In participants without diabetes, the hazard ratios for statin use in 75-84 year olds were 0.94 (95% confidence interval 0.86 to 1.04) for atherosclerotic CVD and 0.98 (0.91 to 1.05) for all cause mortality, and in those aged 85 and older were 0.93 (0.82 to 1.06) and 0.97 (0.90 to 1.05), respectively. In participants with diabetes, the hazard ratio of statin use in 75-84 year olds was 0.76 (0.65 to 0.89) for atherosclerotic CVD and 0.84 (0.75 to 0.94) for all cause mortality, and in those aged 85 and older were 0.82 (0.53 to 1.26) and 1.05 (0.86 to 1.28), respectively. Similarly, effect analysis of age in a continuous scale, using splines, corroborated the lack of beneficial statins effect for atherosclerotic CVD and all cause mortality in participants without diabetes older than 74 years. In participants with diabetes, statins showed a protective effect against atherosclerotic CVD and all cause mortality; this effect was substantially reduced beyond the age of 85 years and disappeared in nonagenarians. Conclusions In participants older than 74 years without type 2 diabetes, statin treatment was not associated with a reduction in atherosclerotic CVD or in all cause mortality, even when the incidence of atherosclerotic CVD was statistically significantly higher than the risk thresholds proposed for statin use. In the presence of diabetes, statin use was statistically significantly associated with reductions in the incidence of atherosclerotic CVD and in all cause mortality. This effect decreased after age 85 years and disappeared in nonagenarians.

Diabetes and new-onset atrial fibrillation in a hypertensive population

Abstract Aim The association of diabetes with new-onset atrial fibrillation (AF) remains controversial. Hypertension may partly explain the risk association ascribed to diabetes. We studied the role and characteristics of diabetes in hypertensive patients with no ischemic vascular disease. Methods Records of 262,892 persons from the Information System for the Development of Research in Primary Care in Catalonia (Spain) were examined from July 2006 to December 2011. Included participants were ≥55-years-old and hypertensive with no ischemic heart disease, stroke, or peripheral artery disease. We used Cox proportional hazards regression to model incidences in the diabetic and non-diabetic subgroups of our population, and among diabetic patients, diabetes duration and pharmacological treatment, hemoglobin A1C, and body mass index. Results New-onset AF incidence in diabetic patients was 13.3 per 1000 person-years (mean follow-up: 4.3 years). In non-diabetic patients, it was 10.4 per 1000 person-years (mean follow-up: 4.1 years). Diabetes hazard ratio (HR) for new-onset AF was 1.11 (95% confidence interval (CI): 1.06–1.16). Diabetic patients also diagnosed with obesity had an HR of 1.41 (95% CI: 1.22–1.64). Conclusion Diabetes was modestly associated with new-onset AF in hypertensive patients with no ischemic vascular disease. Among diabetic patients, only obesity reached significance in its association with this arrhythmia. Key Messages Diabetes modestly associated with new-onset atrial fibrillation in hypertensive patients with no ischemic vascular disease. In the subgroup of patients with diabetes, only obesity reached significance in its association with atrial fibrillation.

Role of renal function in cardiovascular risk assessment: A retrospective cohort study in a population with low incidence of coronary heart disease

BACKGROUND Early-stage chronic kidney disease (CKD), a marker of cardiovascular risk, is susceptible to therapeutic intervention but need further study in populations with low incidence of coronary heart disease (CHD). Incorporating glomerular filtration rate (GFR) could improve cardiovascular risk prediction in these patients. OBJECTIVE To determine if decreased GFR is associated with increased risk of cardiovascular morbidity and all-cause mortality and to analyse GFR effect on cardiovascular risk prediction in a population with low CHD incidence. METHODS Retrospective, observational, population-based study of 1,081,865 adults (35-74years old). Main exposure variable: GFR. OUTCOMES CHD, cerebrovascular disease, cardiovascular diseases, all-cause mortality. Association between GFR categories of CKD (G1-G5) and outcomes was tested with Cox survival models. G1 was defined as the reference category. Predictive value of GFR was evaluated by integrated discrimination improvement (IDI) and net reclassification improvement (NRI) indices. RESULTS Beginning at stage-3a CKD, increased risk was observed for coronary (HR 1.27 (95%CI 1.14-1.43)), cerebrovascular (HR 1.19 (95%CI 1.06-1.34)), cardiovascular (HR 1.23 (95%CI 1.13-1.34)) and all-cause mortality risk (HR 1.17 (95%CI 1.07-1.27)). GFR did not increase discrimination and reclassification indices significantly for any outcome. CONCLUSION In general population with low CHD incidence and stage-3 CKD, impaired GFR was associated with increased risk of all cardiovascular diseases studied and all-cause mortality, but adding GFR values did not improve cardiovascular risk calculation. Despite a four-fold higher rate of CHD incidence at GFR G3a compared to G1, this represents moderate cardiovascular risk in our context.

Incident Atrial Fibrillation Hazard in Hypertensive PopulationNovelty and Significance

Determining the risk of atrial fibrillation within the hypertensive population without ischemic vascular disease would aid in decision making on preventive approaches. Accordingly, we aimed to estimate the risk of incident atrial fibrillation in this population. We conducted an historical cohort study between July 1, 2006, and December 31, 2011, using anonymized longitudinal patient information from primary care and hospital discharge records contained in the System for the Development of Research in Primary Care database. We included 255 440 hypertensive patients, aged ≥55 years at the time of study entry. Individuals with previous atrial fibrillation, ischemic heart disease, stroke, and peripheral artery disease were excluded. To build the incident atrial fibrillation risk function, a derivation and a validation cohort were defined, representing 60% and 40% of the entire database, respectively, and a Cox proportional hazards model was fitted. Atrial fibrillation incidence was 7.24 per 1000 person-years (95% confidence interval, 7.08–7.40). The final model included age, weight, total cholesterol, heart failure, valvular heart disease, and antihypertensive treatment. Its concordance index (standard error) was 0.769 (0.004) and 0.768 (0.005) in the derivation and validation datasets, respectively. This research provides a tool, built with variables from daily clinical practice, that can be readily used in the primary care setting to predict atrial fibrillation incidence in the hypertensive population without ischemic vascular disease. The tool may help tailor individualized diagnostic and preventive care decisions. # Novelty and Significance {#article-title-40}Determining the risk of atrial fibrillation within the hypertensive population without ischemic vascular disease would aid in decision making on preventive approaches. Accordingly, we aimed to estimate the risk of incident atrial fibrillation in this population. We conducted an historical cohort study between July 1, 2006, and December 31, 2011, using anonymized longitudinal patient information from primary care and hospital discharge records contained in the System for the Development of Research in Primary Care database. We included 255 440 hypertensive patients, aged ≥55 years at the time of study entry. Individuals with previous atrial fibrillation, ischemic heart disease, stroke, and peripheral artery disease were excluded. To build the incident atrial fibrillation risk function, a derivation and a validation cohort were defined, representing 60% and 40% of the entire database, respectively, and a Cox proportional hazards model was fitted. Atrial fibrillation incidence was 7.24 per 1000 person-years (95% confidence interval, 7.08–7.40). The final model included age, weight, total cholesterol, heart failure, valvular heart disease, and antihypertensive treatment. Its concordance index (standard error) was 0.769 (0.004) and 0.768 (0.005) in the derivation and validation datasets, respectively. This research provides a tool, built with variables from daily clinical practice, that can be readily used in the primary care setting to predict atrial fibrillation incidence in the hypertensive population without ischemic vascular disease. The tool may help tailor individualized diagnostic and preventive care decisions.