3 research outputs found

    Molecular Subtypes, Metastatic Pattern and Patient Age in Breast Cancer: An Analysis of Italian Network of Cancer Registries (AIRTUM) Data

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    Breast cancer stage at diagnosis, patient age and molecular tumor subtype influence disease progression. The aim of this study was to analyze the relationships between these factors and survival in breast cancer patients among the Italian population using data from the AIRTUM national database. We enrolled women with primary breast cancer from 17 population-based cancer registries. Patients were subdivided into older (>69 years), middle (50–69 years) and younger age groups (<50 years) and their primary tumors categorized into four molecular subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. There were 8831 patients diagnosed between 2010 and 2012 included. The most represented age group was 50–69 years (41.7%). In 5735 cases the molecular subtype was identified: HER2–/HR+ was the most frequent (66.2%) and HER2+/HR− the least (6.2%). Of the 390 women with metastases at diagnosis, 38% had simultaneous involvement of multiple sites, independent of age and molecular profile. In women with a single metastatic site, bone (20% of cases), liver (11%), lung (7%) and brain (3%) were the most frequent. In the studied age groups with different receptor expression profiles, the tumor metastasized to target organs with differing frequencies, affecting survival. Five-year survival was lowest in women with triple-negative (HER2−/HR–) tumors and women with brain metastases at diagnosis

    Complete prevalence and indicators of cancer cure: enhanced methods and validation in Italian population-based cancer registries

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    ObjectivesTo describe the procedures to derive complete prevalence and several indicators of cancer cure from population-based cancer registries. Materials and methodsCancer registry data (47% of the Italian population) were used to calculate limited duration prevalence for 62 cancer types by sex and registry. The incidence and survival models, needed to calculate the completeness index (R) and complete prevalence, were evaluated by likelihood ratio tests and by visual comparison. A sensitivity analysis was conducted to explore the effect on the complete prevalence of using different R indexes. Mixture cure models were used to estimate net survival (NS); life expectancy of fatal (LEF) cases; cure fraction (CF); time to cure (TTC); cure prevalence, prevalent patients who were not at risk of dying as a result of cancer; and already cured patients, those living longer than TTC at a specific point in time. CF was also compared with long-term NS since, for patients diagnosed after a certain age, CF (representing asymptotical values of NS) is reached far beyond the patient's life expectancy. ResultsFor the most frequent cancer types, the Weibull survival model stratified by sex and age showed a very good fit with observed survival. For men diagnosed with any cancer type at age 65-74 years, CF was 41%, while the NS was 49% until age 100 and 50% until age 90. In women, similar differences emerged for patients with any cancer type or with breast cancer. Among patients alive in 2018 with colorectal cancer at age 55-64 years, 48% were already cured (had reached their specific TTC), while the cure prevalence (lifelong probability to be cured from cancer) was 89%. Cure prevalence became 97.5% (2.5% will die because of their neoplasm) for patients alive >5 years after diagnosis. ConclusionsThis study represents an addition to the current knowledge on the topic providing a detailed description of available indicators of prevalence and cancer cure, highlighting the links among them, and illustrating their interpretation. Indicators may be relevant for patients and clinical practice; they are unambiguously defined, measurable, and reproducible in different countries where population-based cancer registries are active
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