title: Estimates of cancer burden in Umbria.
abstract: OBJECTIVE
  Model-based estimates and projections of epidemiological indicators related to cancer are important tools to support public health policies and planning. The aim of the present study is to produce projections of cancer incidence, mortality and prevalence for the Umbria region (900,000 inhabitants) in central Italy.
  
  
  METHODS
  The estimations were obtained by applying the MIAMOD method, a statistical back-calculation approach to derive incidence and prevalence figures starting from mortality and relative survival data. Published data from the Italian cancer registries were modeled in order to estimate regional cancer survival. Estimated incidence rates were validated with observed incidence rates obtained from the Umbria regional cancer registry.
  
  
  RESULTS
  The most frequent cancer sites estimated were colon-rectum, prostate and breast in women, with 970, 615 and 729 new diagnoses, respectively, in 2012. The incidence rates were increasing for female lung cancer, male colorectal cancer, and melanoma. By contrast, the rates have been declining for cervix and stomach cancer. For lung cancer and prostate cancer in men and colorectal cancer in women the rates increased, reaching a peak in different periods, and then decreased. The incidence rates of breast cancer rose, reaching a plateau in the mid 2010s. Favorable mortality trends were predicted for all cancers except skin melanoma and lung cancer in women. The prevalence of cancer was increasing with the only exception of cervical cancer in women and lung cancer in men in the most recent estimation period.
  
  
  CONCLUSIONS
  The scenario found for cancer incidence and prevalence was largely influenced by screening activities, so that increasing or stable incidence rates may reflect active preventive efforts. Aging, screening, and more complex and costly treatments pose a problem of sustainability and selection of interventions to the regional oncology system. Evaluation of effectiveness of intervention and cost-benefit analyses will be important to ensure cancer control in the future.
authors.forename: Fabrizio
authors.initials: F
authors.lastname: Stracci
authors.forename: Maria Saba
authors.initials: MS
authors.lastname: Petrucci
authors.forename: Roberta
authors.initials: R
authors.lastname: Ciampichini
authors.forename: Andrea
authors.initials: A
authors.lastname: Tavilla
authors.forename: Roberto
authors.initials: R
authors.lastname: Foschi
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000453:epidemiology; D015179:Colorectal Neoplasms / Q000453:epidemiology; D017281:Cost of Illness; D005260:Female; D006801:Humans; D015994:Incidence; D007558:Italy / Q000453:epidemiology; D008175:Lung Neoplasms / Q000453:epidemiology; D008297:Male; D008545:Melanoma / Q000453:epidemiology; D008875:Middle Aged; D009369:Neoplasms / Q000453:epidemiology* / Q000401:mortality; D015995:Prevalence; D011471:Prostatic Neoplasms / Q000453:epidemiology; D012042:Registries; D017678:Sex Distribution; D012878:Skin Neoplasms / Q000453:epidemiology; D013274:Stomach Neoplasms / Q000453:epidemiology; D015996:Survival Rate / Q000639:trends; D002583:Uterine Cervical Neoplasms / Q000453:epidemiology