Correcting inaccurate background mortality in excess hazard models through breakpoints

A new cure model that corrects for increased risk of non-cancer death: analysis of reliability and robustness, and application to real-life data

BACKGROUND

Non-cancer mortality in cancer patients may be higher than overall mortality in the general population due to a combination of factors, such as long-term adverse effects of treatments, and genetic, environmental or lifestyle-related factors. If so, conventional indicators may underestimate net survival and cure fraction. Our aim was to propose and evaluate a mixture cure survival model that takes into account the increased risk of non-cancer death for cancer patients.

METHODS

We assessed the performance of a corrected mixture cure survival model derived from a conventional mixture cure model to estimate the cure fraction, the survival of uncured patients, and the increased risk of non-cancer death in two settings of net survival estimation, grouped life-table data and individual patients' data. We measured the model's performance in terms of bias, standard deviation of the estimates and coverage rate, using an extensive simulation study. This study included reliability assessments through violation of some of the model's assumptions. We also applied the models to colon cancer data from the FRANCIM network.

RESULTS

When the assumptions were satisfied, the corrected cure model provided unbiased estimates of parameters expressing the increased risk of non-cancer death, the cure fraction, and net survival in uncured patients. No major difference was found when the model was applied to individual or grouped data. The absolute bias was < 1% for all parameters, while coverage ranged from 89 to 97%. When some of the assumptions were violated, parameter estimates appeared more robust when obtained from grouped than from individual data. As expected, the uncorrected cure model performed poorly and underestimated net survival and cure fractions in the simulation study. When applied to colon cancer real-life data, cure fractions estimated using the proposed model were higher than those in the conventional model, e.g. 5% higher in males at age 60 (57% vs. 52%).

CONCLUSIONS

The present analysis supports the use of the corrected mixture cure model, with the inclusion of increased risk of non-cancer death for cancer patients to provide better estimates of indicators based on cancer survival. These are important to public health decision-making; they improve patients' awareness and facilitate their return to normal life.

Difference in net survival using regional and national life tables in Japan

BACKGROUND

National life table is commonly used for estimating cancer net survival. However, the national life table does not reflect condition of people in local area accurately, because there are disparities in cancer mortality rates among the local area in many cases. We investigated magnitude of difference in cancer net survival using the local area in Japan and Japanese life tables.

METHODS

We analyzed data from 32,942 cancer patients diagnosed between 2010 and 2012 in Aomori prefecture, Japan. Expected survival rates in Aomori (ESA) and Japan (ESJ) were estimated based on the life table of each area. Five-year net survival rates using ESA and the ESJ were estimated using the Pohar-Perme method.

RESULTS

The difference between net survival rates using the ESA (NSA) and the ESJ (NSJ) were larger than in men (0.3－3.0%) than in women (0.1－0.8%). The largest difference in the net survival rate was observed in prostate cancer patients, because the difference in the expected survival in oldest old men was remarkable.

CONCLUSION

Two factors affected the difference in the net survival rates resulting from the sensitivity analysis. The difference was larger (1) among older patients or (2) with a longer observation period (person-years).