Cancer Causes & Control

, Volume 25, Issue 3, pp 365–373 | Cite as

Site-specific proportion cured models applied to cancer registry data

  • Michael EdlingerEmail author
  • Hanno Ulmer
  • Milada Cvancarova
  • Willi Oberaigner
Original paper



Proportion-cured models were applied to evaluate their applicability on data from a relatively small cancer registry and to assess the up-to-date survival level of major cancer types in Tyrol, Austria.


In total, the 25 most common types of cancer were analyzed with mixture cure models using the period approach for estimation of the proportion cured and median survival time of the fatal cases.


For several of the cancer types, no estimates could be obtained. The models converged for 14 sites among females and for 15 among males. The highest estimate of the proportion cured was found for cervix cancer (74.0 %; 95 % CI 64.4–83.6) and the lowest for male pancreas cancer (4.6 %; 95 % CI 0.2–9.0). The highest median survival of the uncured was 2.7 years (95 % CI 1.2–6.0) for male larynx cancer and the lowest 0.3 years (95 % CI 0.1–0.6) for male acute myeloblastic leukemia (AML).


The estimates seem reliable for stomach, colon, rectum, pancreas, lung, cervix, ovary, central nervous system/brain and AML cancer and among men also for head/neck, esophagus, liver and kidney cancer. Altogether, it is demonstrated that even data from a regional cancer registry covering a rather small region can be utilized to derive up-to-date survival estimates of various cancer types, enabling monitoring of the development and changes in cancer treatment. Moreover, potentially this methodology is advantageously employable in any situation where the number of cancer cases is limited.


Site-specific cancer survival Proportion cured Survival time uncured Cancer registry Epidemiology 



Acute lymphoblastic leukemia


Acute myeloblastic leukemia


Chronic lymphoid leukemia


Central nervous system


Non-Hodgkin lymphoma


Non-melanoma skin cancer



We thank Lois Harrasser sincerely for his good work managing the data.

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michael Edlinger
    • 1
    Email author
  • Hanno Ulmer
    • 1
  • Milada Cvancarova
    • 2
    • 3
  • Willi Oberaigner
    • 4
  1. 1.Department of Medical Statistics, Informatics, and Health EconomicsInnsbruck Medical UniversityInnsbruckAustria
  2. 2.Cancer Registry of NorwayInstitute of Population-based Cancer ResearchOsloNorway
  3. 3.Department of OncologyOslo University HospitalOsloNorway
  4. 4.Cancer Registry of TyrolTILAKInnsbruckAustria

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