What is the Most Suitable Time Period to Assess the Time Trends in Cancer Incidence Rates to Make Valid Predictions--an Empirical Approach

Asian Pac J Cancer Prev. 2015;16(8):3097-100. doi: 10.7314/apjcp.2015.16.8.3097.


Projections of cancer cases are particularly useful in developing countries to plan and prioritize both diagnostic and treatment facilities. In the prediction of cancer cases for the future period say after 5 years or after 10 years, it is imperative to use the knowledge of past time trends in incidence rates as well as in population at risk. In most of the recently published studies the duration for which the time trend was assessed was more than 10 years while in few studies the duration was between 5-7 years. This raises the question as to what is the optimum time period which should be used for assessment of time trends and projections. Thus, the present paper explores the suitability of different time periods to predict the future rates so that the valid projections of cancer burden can be done for India. The cancer incidence data of selected cancer sites of Bangalore, Bhopal, Chennai, Delhi and Mumbai PBCR for the period of 1991-2009 was utilized. The three time periods were selected namely 1991-2005; 1996-2005, 1999-2005 to assess the time trends and projections. For the five selected sites, each for males and females and for each registry, the time trend was assessed and the linear regression equation was obtained to give prediction for the years 2006, 2007, 2008 and 2009. These predictions were compared with actual incidence data. The time period giving the least error in prediction was adjudged as the best. The result of the current analysis suggested that for projections of cancer cases, the 10 years duration data are most appropriate as compared to 7 year or 15 year incidence data.

MeSH terms

  • Empirical Research*
  • Female
  • Follow-Up Studies
  • Humans
  • Incidence
  • India / epidemiology
  • Male
  • Neoplasm Staging
  • Neoplasms / epidemiology*
  • Neoplasms / pathology*
  • Prognosis
  • Registries
  • Risk Assessment
  • Time Factors