BACKGROUND: EUROCARE found marked differences in cancer survival across European populations, provoking extensive discussion as to the cause. We investigated the influence of socioeconomic indicators on survival, making use of the indicator population-based age-standardized and cancer site-standardized relative survival for all cancers combined (all cancer survival). METHODS: Bivariate correlation and multivariate regression analyses investigated relations between 1995 socioeconomic variables and all cancer survival in EUROCARE-3 patients from 19 European countries diagnosed 1990-94 and followed to 1999. RESULTS: Gross domestic product (GDP) and total national expenditure on health (TNEH) correlated highly with all cancer survival. Wealthy northern and western European countries had high survival; eastern European countries had low all cancer survival. GDP, TNEH, and number of computed tomography scanners per million--proxy of technological investment in cancer care--explained most survival differences. Low all cancer survival in the UK and Denmark compared to countries of similar wealth was closely related to fewer computed tomography scanners. Low all cancer survival in Poland compared to countries of similar wealth was also related to low TNEH. CONCLUSIONS: All cancer survival appears a useful and important indicator for monitoring countries' performance in cancer control. The most direct way for poorer European countries to improve all cancer survival would be to get richer; for richer countries more investment in health technology is important. However the sharply increasing costs of cancer care may render this impossible suggesting the need to radically rethink cancer control strategies.
BACKGROUND: EUROCARE found marked differences in cancer survival across European populations, provoking extensive discussion as to the cause. We investigated the influence of socioeconomic indicators on survival, making use of the indicator population-based age-standardized and cancer site-standardized relative survival for all cancers combined (all cancer survival). METHODS: Bivariate correlation and multivariate regression analyses investigated relations between 1995 socioeconomic variables and all cancer survival in EUROCARE-3 patients from 19 European countries diagnosed 1990-94 and followed to 1999. RESULTS: Gross domestic product (GDP) and total national expenditure on health (TNEH) correlated highly with all cancer survival. Wealthy northern and western European countries had high survival; eastern European countries had low all cancer survival. GDP, TNEH, and number of computed tomography scanners per million--proxy of technological investment in cancer care--explained most survival differences. Low all cancer survival in the UK and Denmark compared to countries of similar wealth was closely related to fewer computed tomography scanners. Low all cancer survival in Poland compared to countries of similar wealth was also related to low TNEH. CONCLUSIONS: All cancer survival appears a useful and important indicator for monitoring countries' performance in cancer control. The most direct way for poorer European countries to improve all cancer survival would be to get richer; for richer countries more investment in health technology is important. However the sharply increasing costs of cancer care may render this impossible suggesting the need to radically rethink cancer control strategies.
Authors: Flavie Bompaire; Marion Lahutte; Stephane Buffat; Carole Soussain; Anne Emmanuelle Ardisson; Robert Terziev; Magali Sallansonnet-Froment; Thierry De Greslan; Sébastien Edmond; Mehdi Saad; Christophe Nioche; Thomas Durand; Sonia Alamowitch; Khe Hoang Xuan; Jean Yves Delattre; Jean Luc Renard; Hervé Taillia; Cyrus Chargari; Dimitri Psimaras; Damien Ricard Journal: Support Care Cancer Date: 2018-07-07 Impact factor: 3.603
Authors: Hannah K Weir; Christopher J Johnson; Angela B Mariotto; Donna Turner; Reda J Wilson; Diane Nishri; Kevin C Ward Journal: J Natl Cancer Inst Monogr Date: 2014-11
Authors: Charles Swanton; James M Larkin; Marco Gerlinger; Aron C Eklund; Michael Howell; Gordon Stamp; Julian Downward; Martin Gore; P Andrew Futreal; Bernard Escudier; Fabrice Andre; Laurence Albiges; Benoit Beuselinck; Stephane Oudard; Jens Hoffmann; Balázs Gyorffy; Chris J Torrance; Karen A Boehme; Hansjuergen Volkmer; Luisella Toschi; Barbara Nicke; Marlene Beck; Zoltan Szallasi Journal: Genome Med Date: 2010-08-11 Impact factor: 11.117