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Cancer Trends Progress Report – 2009/2010 Update

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Survival Estimation Methods
Appendices

In Figure L1 of this report, the most recent 5-year estimates of survival are for patients diagnosed in 2001. The estimates are slightly dated due to the lag time in cancer registry reporting of new cases and the time it takes to observe 5-year survival. Because complete follow-up is available only through 2005, the most recent estimates are based on data as follows:

Survival Time Diagnosis Year
1 year 2005
2 years 2004
3 years 2003
4 years 2002
5 years 2001

Researchers at the National Cancer Institute (NCI) and elsewhere have been considering methods for extrapolating to obtain long-term survival estimates for cases diagnosed. Two such methods are the period method and the modeled method.

Figure L1a displays a graph of 5-year relative survival rates for all cancer sites combined, 1975-1997. The graph also shows point estimates for the years 1998-2001, using the period method and modeled method described in the text.

The period method, introduced by Brenner et al. (1) and slightly modified for use with Surveillance, Epidemiology, and End Results (SEER) data (2), considers only the patients' survival experience within the most recent calendar period (i.e., 2003–2005). For example, to estimate the 5-year survival in 2005, we use 0- to 1-year survival experience for cases diagnosed in (2003–2005), 1- to 2-year survival experience for cases diagnosed in (2002–2004), who survived at least 1 year, and so on up to 4- to 5- year survival experience for cases diagnosed in (1999–2001), who survived at least 4 years. The period 5-year survival is then calculated by multiplying these interval survival probabilities. The period method was not developed to provide survival trend but to give the most up-to-date estimate of survival experience observed in the data. The period method estimate is plotted as a filled diamond in the figure above.

The modeled method (3–4) consists of fitting a trend line across diagnosis years to each of the five observed interval survival probabilities (e.g., the 0- to 1-year survival for cases diagnosed in 2001 to 2005, 1- to 2-year survival for cases diagnosed in 2001 to 2004, etc.). These trend lines are then projected to the year of interest. The final estimate for a particular diagnosis year is obtained by multiplying the known and projected interval survival probabilities together.

For example, to estimate the 5-year survival rate for those diagnosed in 2005 using available data, known 0- to 1-year survival rates are combined with 1- to 2-, 2- to 3-, 3- to 4-, and 4- to 5-year projections from the model. The advantage of this method is that if survival is improving over time, the 4- to 5-year estimate of survival used for the 2005 computation will more accurately reflect the improved trend compared to the 2001 estimate used in the period method. The 5-year modeled survival estimates are plotted as open squares in the figure above. Because these projections combine known survival probabilities with projections, they are not a simple extrapolation of the last segment estimated using joinpoint regression.

These methods have the potential to provide clinicians, patients, cancer control analysts, and policy makers improved estimates of the long-term prognoses of recently diagnosed patients. As researchers continue to refine survival estimation methods and examine their assumptions and predictive ability, we ask for your input. Please click here to provide feedback.

References

  1. Brenner H. Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis. Lancet 2002;360(9340):1131–5.
  2. Cronin K, Mariotto A, Scoppa S, Green D, Clegg L. Differences Between Brenner et al. and NCI Methods for Calculating Period Survival. Technical Report # 2003-02, Statistical Research and Applications Branch, National Cancer Institute 2003 (http://srab.cancer.gov/reports).
  3. Cronin K, Feuer E, Wesley M, Mariotto A, Scoppa S, Green D. Current Estimates for 5 and 10 Year Relative Survival. Technical Report # 2003-04, Statistical Research and Applications Branch, National Cancer Institute 2003 (http://srab.cancer.gov/reports).
  4. Mariotto A, Wesley MN, Cronin KA, Johnson KA., Feuer EJ. Estimates of long-term survival for newly diagnosed cancer patients: a projection approach. Cancer 2006;106 (9);2039–50.

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