Methodological issues in estimating survival in patients with multiple primary cancers: an application to women with breast cancer as a first tumour

<p>Abstract</p> <p>Background</p> <p>Comparing survival of patients with a single tumour and patients with multiple primaries poses different methodological problems. In population based studies, where we cannot rely on detailed clinical information, the issue is disentangling the share of survival probability from the first and second cancer, and their compounded effect. We examined three hypotheses: A) the survival probability since the first tumour does not change with the occurrence of a second tumour; B) the probability of surviving a tumour does not change with the presence of a previous primary; C) the probabilities of surviving two subsequent primary tumours are independent (additivity hypothesis on mortality rates).</p> <p>Methods</p> <p>We studied the survival probabilities modelling mortality rates according to hypotheses A), B) and C). Mortality rates were calculated using Aalen-Johansen estimators which allowed to discount for the lag-time survival before developing a second tumour. We applied this approach to a cohort of 436 women with breast cancer (BC) and a subsequent tumour in the resident population of Turin, Italy, between 1985 and 2002.</p> <p>Results</p> <p>We presented our results in term of a Standardised Mortality Ratio calculated (<it>SMR</it>_<it>AJ</it>) after 10 years of follow-up. For hypothesis A we observed a significant excess mortality of 2.21 (95% C.I. 1.94 – 2.45). Concerning hypothesis B we found a not significant <it>SMR</it>_{<it>AJ </it>}of 0.98 (95% C.I. 0.87 – 1.10). The additivity hypothesis (C) was not confirmed as it overestimated the risk of death, in fact <it>SMRs</it>_{<it>AJ </it>}were all below 1: 0.75 (95% C.I. 0.66 – 0.84) for BC and all subsequent cancers, 0.72 (95% C.I. 0.55 – 0.94) for BC and colon-rectum cancer, 0.76 (95% C.I. 0.48 – 1.14) for BC and corpus uteri cancer (not significant).</p> <p>Conclusion</p> <p>This method proved to be useful in disentangling the effect of different subsequent cancers on mortality. In our application it shows a worse long-term mortality for women with two cancers than that with BC only. However, the increase in mortality was lower than expected under the additivity assumption.</p