• F Berrino, A Micheli, M Sant, and R Capocaccia.
• Divisione di Epidemiologia, Istituto Nazionale per lo Studio e la Cura dei Tumori, Milan, Italy. INTEPI@ICIL64.CILEA.IT
• Tumori. 1997 Jan 1; 83 (1): 9-16.

AbstractSince 1990 a concerted action between European population-based cancer registries (the EUROCARE project) has been carried out with the aims of establishing whether there are differences in cancer patient survival in Europe, and the reasons for such differences. Survival differences actually exist for cancer sites for which the stage of disease at diagnosis is the major prognostic factor (such as breast, stomach and colon cancer). However, for most cancer sites, survival increases over time and the survival rates of different countries tend to converge towards higher values. Interpreting survival differences and trends is not an easy task. Longer survival may be achieved by postponing death through better treatment or by anticipating diagnosis. However, an earlier diagnosis may or may not make a treatment more effective in postponing death. The computation of stage-specific or stage-adjusted survival is not sufficient for interpretation of survival differences, because staging procedures change over time and may vary in different hospitals and countries. In addition to an early diagnosis and more effective treatment, a number of factors may bias survival estimates. They may be classified into factors that can be controlled in the analysis (at least partially), such as mortality from other causes, demographic factors, epoch of diagnosis, different statistical methodology, and factors depending on the validity of cancer registry data, such as definition of the illness, exhaustiveness and quality of registration, completeness of follow-up, definition of the data of diagnosis, and definition of disease stage including the diagnostic procedure used to establish stage. To help disentangle the effects of early diagnosis and better treatment, several statistical approaches are being developed: multivariate analysis on relative survival data, new modeling analysis to separately estimate the proportion of cured patients and the length of survival for those patients destined to die, and the standardized collection of information on stage at diagnosis and staging procedures.

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