AIM: Overall survival after cancer is frequently used when assessing the health care service performance as a whole. While used by the public, politicians, and the media, it is often discarded by clinicians and epidemiologists due to the heterogeneous mix of different cancers, risk factors and treatment modalities. We studied the trend in the Nordic 5-year relative survival and excess mortality for all cancers combined to see if the impact of case-mix and variations between countries in diagnostic methods such as breast screening and PSA testing could explain the lower survival in Denmark. MATERIAL AND METHODS: From the NORDCAN database 1964-2003, we defined two cohorts of cancer patients, one excluding non-melanoma skin cancer and another also excluding breast and prostate cancer. We estimated age-standardised incidence and mortality rates, 5-year relative survival, and excess mortality rates for varying follow-up periods, and age-specific 5-year relative survival by country, sex and 5-year diagnostic period. RESULTS: Prostate cancer is the main driver of the incidence increase in men, as do breast cancer in women, whereas cancer mortality in all Nordic countries is declining. The 5-year relative survival ratios are increasing in each Nordic population, but less so in Denmark. Country differences in survival stem mainly from follow-up periods immediately after diagnosis. Adjusting for the case-mix of diagnoses diminished differences a little while exclusion of breast and prostate cancer reduced the gap between countries in survival and excess mortality more considerably, yet post-adjustment, Danish patients still fare worse during the first three months after diagnosis. CONCLUSION: Adjustment for case-mix and exclusion of sites where diagnostic procedures change the pattern of incidence is important when comparing overall cancer survival across countries, but the correction only explains part of the observed differences in survival. Other factors such as stage at presentation, co-morbidity, tobacco and alcohol consumption are likely contributors.
AIM: Overall survival after cancer is frequently used when assessing the health care service performance as a whole. While used by the public, politicians, and the media, it is often discarded by clinicians and epidemiologists due to the heterogeneous mix of different cancers, risk factors and treatment modalities. We studied the trend in the Nordic 5-year relative survival and excess mortality for all cancers combined to see if the impact of case-mix and variations between countries in diagnostic methods such as breast screening and PSA testing could explain the lower survival in Denmark. MATERIAL AND METHODS: From the NORDCAN database 1964-2003, we defined two cohorts of cancerpatients, one excluding non-melanoma skin cancer and another also excluding breast and prostate cancer. We estimated age-standardised incidence and mortality rates, 5-year relative survival, and excess mortality rates for varying follow-up periods, and age-specific 5-year relative survival by country, sex and 5-year diagnostic period. RESULTS:Prostate cancer is the main driver of the incidence increase in men, as do breast cancer in women, whereas cancer mortality in all Nordic countries is declining. The 5-year relative survival ratios are increasing in each Nordic population, but less so in Denmark. Country differences in survival stem mainly from follow-up periods immediately after diagnosis. Adjusting for the case-mix of diagnoses diminished differences a little while exclusion of breast and prostate cancer reduced the gap between countries in survival and excess mortality more considerably, yet post-adjustment, Danish patients still fare worse during the first three months after diagnosis. CONCLUSION: Adjustment for case-mix and exclusion of sites where diagnostic procedures change the pattern of incidence is important when comparing overall cancer survival across countries, but the correction only explains part of the observed differences in survival. Other factors such as stage at presentation, co-morbidity, tobacco and alcohol consumption are likely contributors.
Authors: Hilde Jensvoll; Marianne T Severinsen; Jens Hammerstrøm; Sigrid K Brækkan; Søren R Kristensen; Suzanne C Cannegieter; Kristine Blix; Anne Tjønneland; Frits R Rosendaal; Olga Dziewiecka; Kim Overvad; Inger Anne Næss; John-Bjarne Hansen Journal: Clin Epidemiol Date: 2015-09-16 Impact factor: 4.790