Characteristics of people living in Italy after a cancer diagnosis in 2010 and projections to 2020

BACKGROUND: Estimates of cancer prevalence are widely based on limited duration, often including patients living after a cancer diagnosis made in the previous 5 years and less frequently on complete prevalence (i.e., including all patients regardless of the time elapsed since diagnosis). This study aims to provide estimates of complete cancer prevalence in Italy by sex, age, and time since diagnosis for all cancers combined, and for selected cancer types. Projections were made up to 2020, overall and by time since diagnosis. METHODS: Data were from 27 Italian population-based cancer registries, covering 32% of the Italian population, able to provide at least 7 years of registration as of December 2009 and follow-up of vital status as of December 2013. The data were used to compute the limited-duration prevalence, in order to estimate the complete prevalence by means of the COMPREV software. RESULTS: In 2010, 2,637,975 persons were estimated to live in Italy after a cancer diagnosis, 1.2 million men and 1.4 million women, or 4.6% of the Italian population. A quarter of male prevalent cases had prostate cancer (n\u2009=\u2009305,044), while 42% of prevalent women had breast cancer (n\u2009=\u2009604,841). More than 1.5 million people (2.7% of Italians) were alive since 5 or more years after diagnosis and 20% since 6515 years. It is projected that, in 2020 in Italy, there will be 3.6 million prevalent cancer cases (+\u200937% vs 2010). The largest 10-year increases are foreseen for prostate (+\u200985%) and for thyroid cancers (+\u200979%), and for long-term survivors diagnosed since 20 or more years (+\u200945%). Among the population aged 6575 years, 22% will have had a previous cancer diagnosis. CONCLUSIONS: The number of persons living after a cancer diagnosis is estimated to rise of approximately 3% per year in Italy. The availability of detailed estimates and projections of the complete prevalence are intended to help the implementation of guidelines aimed to enhance the long-term follow-up of cancer survivors and to contribute their rehabilitation need

Association of Mild Anemia with Cognitive, Functional, Mood and Quality of Life Outcomes in the Elderly: The “Health and Anemia” Study

BACKGROUND: In the elderly persons, hemoglobin concentrations slightly below the lower limit of normal are common, but scant evidence is available on their relationship with significant health indicators. The objective of the present study was to cross-sectionally investigate the association of mild grade anemia with cognitive, functional, mood, and quality of life (QoL) variables in community-dwelling elderly persons. METHODS: Among the 4,068 eligible individuals aged 65-84 years, all persons with mild anemia (n = 170) and a randomly selected sample of non-anemic controls (n = 547) were included in the study. Anemia was defined according to World Health Organization (WHO) criteria and mild grade anemia was defined as a hemoglobin concentration between 10.0 and 11.9 g/dL in women and between 10.0 and 12.9 g/dL in men. Cognition and functional status were assessed using measures of selective attention, episodic memory, cognitive flexibility and instrumental and basic activities of daily living. Mood and QoL were evaluated by means of the Geriatric Depression Scale-10, the Short-Form health survey (SF-12), and the Functional Assessment of Cancer Therapy-Anemia. RESULTS: In univariate analyses, mild anemic elderly persons had significantly worse results on almost all cognitive, functional, mood, and QoL measures. In multivariable logistic regressions, after adjustment for a large number of demographic and clinical confounders, mild anemia remained significantly associated with measures of selective attention and disease-specific QoL (all fully adjusted p<.046). When the lower limit of normal hemoglobin concentration according to WHO criteria was raised to define anemia (+0.2 g/dL), differences between mild anemic and non anemic elderly persons tended to increase on almost every variable. CONCLUSIONS: Cross-sectionally, mild grade anemia was independently associated with worse selective attention performance and disease-specific QoL ratings

ITALIAN CANCER FIGURES - REPORT 2015: The burden of rare cancers in Italy = I TUMORI IN ITALIA - RAPPORTO 2015: I tumori rari in Italia

OBJECTIVES: This collaborative study, based on data collected by the network of Italian Cancer Registries (AIRTUM), describes the burden of rare cancers in Italy. Estimated number of new rare cancer cases yearly diagnosed (incidence), proportion of patients alive after diagnosis (survival), and estimated number of people still alive after a new cancer diagnosis (prevalence) are provided for about 200 different cancer entities. MATERIALS AND METHODS: Data herein presented were provided by AIRTUM population- based cancer registries (CRs), covering nowadays 52% of the Italian population. This monograph uses the AIRTUM database (January 2015), which includes all malignant cancer cases diagnosed between 1976 and 2010. All cases are coded according to the International Classification of Diseases for Oncology (ICD-O-3). Data underwent standard quality checks (described in the AIRTUM data management protocol) and were checked against rare-cancer specific quality indicators proposed and published by RARECARE and HAEMACARE (www.rarecarenet.eu; www.haemacare.eu). The definition and list of rare cancers proposed by the RARECAREnet "Information Network on Rare Cancers" project were adopted: rare cancers are entities (defined as a combination of topographical and morphological codes of the ICD-O-3) having an incidence rate of less than 6 per 100,000 per year in the European population. This monograph presents 198 rare cancers grouped in 14 major groups. Crude incidence rates were estimated as the number of all new cancers occurring in 2000-2010 divided by the overall population at risk, for males and females (also for gender-specific tumours).The proportion of rare cancers out of the total cancers (rare and common) by site was also calculated. Incidence rates by sex and age are reported. The expected number of new cases in 2015 in Italy was estimated assuming the incidence in Italy to be the same as in the AIRTUM area. One- and 5-year relative survival estimates of cases aged 0-99 years diagnosed between 2000 and 2008 in the AIRTUM database, and followed up to 31 December 2009, were calculated using complete cohort survival analysis. To estimate the observed prevalence in Italy, incidence and follow-up data from 11 CRs for the period 1992-2006 were used, with a prevalence index date of 1 January 2007. Observed prevalence in the general population was disentangled by time prior to the reference date (≤2 years, 2-5 years, ≤15 years). To calculate the complete prevalence proportion at 1 January 2007 in Italy, the 15-year observed prevalence was corrected by the completeness index, in order to account for those cancer survivors diagnosed before the cancer registry activity started. The completeness index by cancer and age was obtained by means of statistical regression models, using incidence and survival data available in the European RARECAREnet data. RESULTS: In total, 339,403 tumours were included in the incidence analysis. The annual incidence rate (IR) of all 198 rare cancers in the period 2000-2010 was 147 per 100,000 per year, corresponding to about 89,000 new diagnoses in Italy each year, accounting for 25% of all cancer. Five cancers, rare at European level, were not rare in Italy because their IR was higher than 6 per 100,000; these tumours were: diffuse large B-cell lymphoma and squamous cell carcinoma of larynx (whose IRs in Italy were 7 per 100,000), multiple myeloma (IR: 8 per 100,000), hepatocellular carcinoma (IR: 9 per 100,000) and carcinoma of thyroid gland (IR: 14 per 100,000). Among the remaining 193 rare cancers, more than two thirds (No. 139) had an annual IR &lt;0.5 per 100,000, accounting for about 7,100 new cancers cases; for 25 cancer types, the IR ranged between 0.5 and 1 per 100,000, accounting for about 10,000 new diagnoses; while for 29 cancer types the IR was between 1 and 6 per 100,000, accounting for about 41,000 new cancer cases. Among all rare cancers diagnosed in Italy, 7% were rare haematological diseases (IR: 41 per 100,000), 18% were solid rare cancers. Among the latter, the rare epithelial tumours of the digestive system were the most common (23%, IR: 26 per 100,000), followed by epithelial tumours of head and neck (17%, IR: 19) and rare cancers of the female genital system (17%, IR: 17), endocrine tumours (13% including thyroid carcinomas and less than 1% with an IR of 0.4 excluding thyroid carcinomas), sarcomas (8%, IR: 9 per 100,000), central nervous system tumours and rare epithelial tumours of the thoracic cavity (5%with an IR equal to 6 and 5 per 100,000, respectively). The remaining (rare male genital tumours, IR: 4 per 100,000; tumours of eye, IR: 0.7 per 100,000; neuroendocrine tumours, IR: 4 per 100,000; embryonal tumours, IR: 0.4 per 100,000; rare skin tumours and malignant melanoma of mucosae, IR: 0.8 per 100,000) each constituted &lt;4% of all solid rare cancers. Patients with rare cancers were on average younger than those with common cancers. Essentially, all childhood cancers were rare, while after age 40 years, the common cancers (breast, prostate, colon, rectum, and lung) became increasingly more frequent. For 254,821 rare cancers diagnosed in 2000-2008, 5-year RS was on average 55%, lower than the corresponding figures for patients with common cancers (68%). RS was lower for rare cancers than for common cancers at 1 year and continued to diverge up to 3 years, while the gap remained constant from 3 to 5 years after diagnosis. For rare and common cancers, survival decreased with increasing age. Five-year RS was similar and high for both rare and common cancers up to 54 years; it decreased with age, especially after 54 years, with the elderly (75+ years) having a 37% and 20% lower survival than those aged 55-64 years for rare and common cancers, respectively. We estimated that about 900,000 people were alive in Italy with a previous diagnosis of a rare cancer in 2010 (prevalence). The highest prevalence was observed for rare haematological diseases (278 per 100,000) and rare tumours of the female genital system (265 per 100,000). Very low prevalence (&lt;10 prt 100,000) was observed for rare epithelial skin cancers, for rare epithelial tumours of the digestive system and rare epithelial tumours of the thoracic cavity. COMMENTS: One in four cancers cases diagnosed in Italy is a rare cancer, in agreement with estimates of 24% calculated in Europe overall. In Italy, the group of all rare cancers combined, include 5 cancer types with an IR&gt;6 per 100,000 in Italy, in particular thyroid cancer (IR: 14 per 100,000).The exclusion of thyroid carcinoma from rare cancers reduces the proportion of them in Italy in 2010 to 22%. Differences in incidence across population can be due to the different distribution of risk factors (whether environmental, lifestyle, occupational, or genetic), heterogeneous diagnostic intensity activity, as well as different diagnostic capacity; moreover heterogeneity in accuracy of registration may determine some minor differences in the account of rare cancers. Rare cancers had worse prognosis than common cancers at 1, 3, and 5 years from diagnosis. Differences between rare and common cancers were small 1 year after diagnosis, but survival for rare cancers declined more markedly thereafter, consistent with the idea that treatments for rare cancers are less effective than those for common cancers. However, differences in stage at diagnosis could not be excluded, as 1- and 3-year RS for rare cancers was lower than the corresponding figures for common cancers. Moreover, rare cancers include many cancer entities with a bad prognosis (5-year RS &lt;50%): cancer of head and neck, oesophagus, small intestine, ovary, brain, biliary tract, liver, pleura, multiple myeloma, acute myeloid and lymphatic leukaemia; in contrast, most common cancer cases are breast, prostate, and colorectal cancers, which have a good prognosis. The high prevalence observed for rare haematological diseases and rare tumours of the female genital system is due to their high incidence (the majority of haematological diseases are rare and gynaecological cancers added up to fairly high incidence rates) and relatively good prognosis. The low prevalence of rare epithelial tumours of the digestive system was due to the low survival rates of the majority of tumours included in this group (oesophagus, stomach, small intestine, pancreas, and liver), regardless of the high incidence rate of rare epithelial cancers of these sites. This AIRTUM study confirms that rare cancers are a major public health problem in Italy and provides quantitative estimations, for the first time in Italy, to a problem long known to exist. This monograph provides detailed epidemiologic indicators for almost 200 rare cancers, the majority of which (72%) are very rare (IR&lt;0.5 per 100,000). These data are of major interest for different stakeholders. Health care planners can find useful information herein to properly plan and think of how to reorganise health care services. Researchers now have numbers to design clinical trials considering alternative study designs and statistical approaches. Population-based cancer registries with good quality data are the best source of information to describe the rare cancer burden in a population

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

AIRTUM e SIE insieme per una definizione condivisa dei tumori emolinfopoietici [AIRTUM and SIE for a shared definition of haemolymphopoietic cancers]

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Mortality Prediction in the Oldest Old with Five Different Equations to Estimate Glomerular Filtration Rate: The Health and Anemia Population-based Study.

Kidney function declines considerably with age, but little is known about its clinical significance in the oldest-old.To study the association between reduced glomerular filtration rate (GFR) estimated according to five equations with mortality in the oldest-old.Prospective population-based study.Municipality of Biella, Piedmont, Italy.700 subjects aged 85 and older participating in the "Health and Anemia" Study in 2007-2008.GFR was estimated using five creatinine-based equations: the Cockcroft-Gault (C-G), Modification of Diet in Renal Disease (MDRD), MAYO Clinic, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Berlin Initiative Study-1 (BIS-1). Survival analysis was used to study mortality in subjects with reduced eGFR (<60 mL/min/1.73 m(2)) compared to subjects with eGFR ≥ 60 mL/min/1.73 m(2).Prevalence of reduced GFR was 90.7% with the C-G, 48.1% with MDRD, 23.3% with MAYO, 53.6% with CKD-EPI and 84.4% with BIS-1. After adjustment for confounders, two-year mortality was significantly increased in subjects with reduced eGFR using BIS-1 and C-G equations (adjusted HRs: 2.88 and 3.30, respectively). Five-year mortality was significantly increased in subjects with eGFR <60 mL/min/1.73 m(2) using MAYO, CKD-EPI and, in a graduated fashion in reduced eGFR categories, MDRD. After 5 years, oldest old with an eGFR <30 mL/min/1.73 m(2) showed a significantly higher risk of death whichever equation was used (adjusted HRs between 2.04 and 2.70).In the oldest old, prevalence of reduced eGFR varies noticeably depending on the equation used. In this population, risk of mortality was significantly higher for reduced GFR estimated with the BIS-1 and C-G equations over the short term. Though after five years the MDRD appeared on the whole a more consistent predictor, differences in mortality prediction among equations over the long term were less apparent. Noteworthy, subjects with a severely reduced GFR were consistently at higher risk of death regardless of the equation used to estimate GFR

Age groups and sex adjusted survival by estimated Glomerular Filtration Rate (eGFR) according to a) Cockcroft and Gault equation (C-G); b) Modification of Diet in Renal Disease (MDRD) formula; (c) MAYO Clinic quadratic equation (MAYO); d) Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula; e) Berlin Initiative Study 1 (BIS-1).

<p>Age groups and sex adjusted survival by estimated Glomerular Filtration Rate (eGFR) according to a) Cockcroft and Gault equation (C-G); b) Modification of Diet in Renal Disease (MDRD) formula; (c) MAYO Clinic quadratic equation (MAYO); d) Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula; e) Berlin Initiative Study 1 (BIS-1).</p

Baseline Characteristics of the Study Population (N between 622 and 700).

<p>^a BMI, Body Mass Index</p><p>^b Respiratory failure = use of O₂ or bronchodilators</p><p>^cAnemia was defined by the WHO criteria as hemoglobin concentration <12.0 g/mL in women and <13.0 g/mL in men</p><p>^dBUN, Blood Urea Nitrogen.</p><p>Baseline Characteristics of the Study Population (N between 622 and 700).</p