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doi 10.1700/386.4536

Life tables for world-wide comparison of relative survival for cancer (CONCORD study)

Paolo Baili, Andrea Micheli, Roberta De Angelis, Hannah K Weir, Silvia Francisci, Mariano Santaquilani, Timo Hakulinen, Manuela Quaresma, Michel P Coleman, CONCORD Working Group

¹Descriptive Epidemiology and Health Planning Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; ²Istituto Superiore di Sanità, National Center of Epidemiology, Surveillance and Health Promotion, Cancer Epidemiology Unit, Rome, Italy; ³Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; ⁴Finnish Cancer Registry, Helsinki, Finland; ⁵Cancer Research UK Cancer Survival Group, Non-Communicable Disease Epidemiology Unit, London School of Hygiene and Tropical Medicine, London, UK; ⁶Members of the CONCORD Working Group (see p 667)

Key words: CONCORD, life tables, mortality, relative survival.

abstract

Background. The CONCORD study compares population-based relative survival from cancer using data from cancer registries in five continents. To estimate relative survival, general mortality life tables are required. Available statistics are incomplete, so various approaches are used to construct complete life tables. This article outlines how the life tables were constructed for CONCORD; it compares life expectancy at birth between 101 populations covered by cancer registries in 31 countries and compares the impact of two approaches to the deployment of life tables in relative survival analysis.

Methods. The CONCORD approach, using specific mathematical methods, produced complete (single-year-of-age) life tables by sex, cancer registry area, calendar year (1990-1999) and race (only in the USA). In order to study the impact of different approaches, we compared relative survival in the USA using the US national life table, centered on the relevant census years, and the CONCORD approach. We estimated relative survival in each American participating cancer registry for patients diagnosed with breast (women), colorectal or prostate cancer during 1990-1994 and followed up to 1999.

Results. Average life expectancy at birth during 1990-1999 varied in CONCORD cancer registry areas from 64 to 78 years in males and from 71 to 84 years in females. It increased during the 1990s more in men than in women. In the USA, it was lower in blacks than in whites. Relative survival in American populations was lower with the CONCORD approach, which incorporates trends and geographic variation in background mortality, than with the USA census life tables.

Conclusions. International variation in background mortality by geographic area, calendar time, race, age and sex is wide. We suggest that in international comparisons of cancer relative survival, complete life tables that are specific for cancer registry area, calendar year and race should be used.

Introduction

International comparisons of population-based cancer relative survival provide valuable information about cancer outcomes and progress in cancer control for clinicians, patients and policy-makers¹. Relative survival estimates are included among the cancer control indicators prepared by the European Cancer Health Indicators Project (www.tumori.net/eurochip), designed to improve European cancer information systems and to promote their use in reducing cancer inequalities.

In Europe, the EUROCARE-3 study² provided relative survival estimates for cancer patients with data from population-based cancer registries in 22 countries. In the USA, the Surveillance, Epidemiology and End Results (SEER) Program of the US National Cancer Institute has regularly produced relative survival estimates for participating cancer registries³. Results from the EUROCARE project and the SEER Program have indicated that survival for most adult cancers is higher in the USA than in Europe^4-7.

The CONCORD project, originally designed to provide a systematic comparison of cancer survival between Europe and the USA, has now provided comparable estimates of relative survival for 31 countries in all five continents, covering patients diagnosed in 1990-1994 for four cancers of substantial public health importance: breast cancer in women, and cancers of the colon, rectum and prostate⁸.

Relative survival in a group of cancer patients is defined as the ratio of the observed probability of survival and the expected probability of survival if the cancer patients had been subject only to the all-cause (general) mortality rates in the general population from which they were drawn^9,10. General mortality varies by age (the risk of death in adults increases with age), by sex (men always have higher mortality), by geographic area (the risk of death differs between countries, but also by sub-populations within countries), by year (falling in recent decades in developed countries¹¹) and by race* (e.g., between blacks and whites in the USA¹²). In order to control for background mortality variation in international cancer survival comparisons, the CONCORD protocol¹³ specified that life tables should incorporate death risks for each combination of these variables and should be reconstructed with mathematical methods when they were not directly available from official statistics.

Life tables have been deployed differently to estimate relative survival in Europe (EUROCARE) and in the USA (SEER Program), and this can affect the comparison of relative survival. In both approaches, the life tables used are specific for sex and single year of age. However, in the EUROCARE approach, life tables are also specific for each cancer registry area and each calendar year of the study period¹⁴, whereas in the USA, the SEER Program usually uses the overall US national, race-specific life table centered on the most recent census, for all cancer registry areas in the SEER Program and over a decade (SEER approach). However, the publicly available SEER*Stat software, which provides a convenient procedure for the analysis of SEER data and other cancer registry databases, also allows users to deploy any set of life tables for the calculation of relative survival. The choice of approach reflects the different purpose of the analyses: EUROCARE compares cancer survival in a set of countries with strikingly different economies and health systems¹⁵, whereas the SEER Program compares cancer survival in a set of populations within a single country.

For world-wide comparison of relative survival, in the CONCORD approach, we constructed complete life tables by sex and single calendar year (1990-1999) for all participating cancer registry populations. Race-specific life tables were also reconstructed where possible and where comparable information on race was available for the cancer patients: this only proved possible for the USA.

In this article, we outline (a) how the CONCORD life tables were constructed and document the differences in life expectancy at birth, by participating cancer registry area, calendar year and (in the USA) race. We also show (b) the impact of different approaches to the deployment of life tables for relative survival analysis; we used the US data to show the impact on relative survival estimates of using life tables with the CONCORD approach, by cancer registry area and calendar year, instead of the more usual SEER approach, with a national life table for a decade and for all cancer registry areas.

Material and methods

Data on general mortality by age, sex (and, in the USA, race) and calendar year or period were obtained for 101 registries in 31 countries (Table 1). The data varied considerably in detail by registry. In the USA, CONCORD cancer registries cover 16 states and six metropolitan areas, with populations ranging from 466,000 inhabitants in Wyoming to 31 million in California⁸. These areas were covered either by SEER registries or by registries participating in the US Center for Disease Control and Prevention (CDC) National Program of Cancer Registries (NPCR). Life tables for the USA are produced by the CDC National Center for Health Statistics (NCHS) and are directly available for the entire US population by age, sex, calendar year and race¹⁶. The SEER*Stat database includes data on the population (US state and country) and the number of deaths from all causes by 5-year age class, sex, calendar year and cancer registry area.

(a) The objective was to construct complete life tables containing the probability of death (all causes of death combined) in each country or region, for each calendar year between 1990 and 1999 and, in the USA, by race. We used several standard approaches to produce complete life tables estimating probabilities of death by single year of age by registry (Table 1).

Table 1 - Characteristics of general population mortality data submitted and methods used to estimate complete life tables by single calendar year in the CONCORD study

	Cancer registry	Mortality data submitted			Complete life tables estimated for CONCORD

		Width of age	Highest	Calendar years	Single calendar	Method^b
		bands (yr)	age	or periods^a	years^a
Africa
Algeria	Setif^c	5	100	2000	1990, … 1999	Elandt-Johnson; Fraction

America, Central & South
Brazil	Both registries^d	10	80	1990, ... 1999	1990, ... 1999	Akima
Cuba	Cuba (national)	5	85	1990, ... 1999	1990, ... 1999	Elandt-Johnson

America, North
Canada	British Columbia	15 (for 0-14)	90	1990, ... 1999	1990, ... 1999	Elandt-Johnson
		1 (for 15-44)
		5 (for 45-90)
	Manitoba	1	90	1990, ... 1999	1990, ... 1999	Elandt-Johnson
	Nova Scotia	1 (for 0-70)	90	1990, ... 1999	1990, ... 1999	Elandt-Johnson
		5 (for 70-90)
	Ontario	15 (for 0-14)	90	1990, ... 1999	1990, ... 1999	Elandt-Johnson
		1 (for 15-44)
		5 (for 45-90)
	Saskatchewan	15 (for 0-14)	90	1990, ... 1999	1990, ... 1999	Elandt-Johnson
		1 (for 15-44)
		5 (for 45-90)
USA	All registries^e	5	85	1990, ... 1999	1990, ... 1999	Elandt-Johnson

Asia
Japan	Fukui	5	95	1990-94, 1995-99	1990, ... 1999	Elandt-Johnson; Fraction
	Osaka	1	99	1990, ... 1999	1990, ... 1999	Exponential
	Yamagata	1	90	1991, ... 1994	1991, ... 1994	Elandt-Johnson for adult ages
			99	1990, 1995, ... 1999		No change

Europe^f
Ireland	Ireland (national)	1	105	1985-87, 1990-92,	1990, … 1999	Fraction
				1995-97, 2001-03
The Netherlands	North Netherlands	5	95	1990, … 1999	1990, … 1999	Elandt-Johnson
Switzerland	Three registries^f	1	99	1990, … 1999		No change
UK	Two registries^f	1	99	1989-91, 1998-00	1990, … 1999	Fraction

Oceania
Australia	All registries^g	1	99	1990, ... 1999	1990, ... 1999	Exponential

^a“1991-1995” means that a single data set was provided for that period, whereas “1991, ... 1995” means data were provided for each year from 1991 to 1995 inclusive. ^bExponential, to obtain death probabilities from death rates; Elandt-Johnson, to obtain complete life tables from abridged (5-year) life tables; Elandt-Johnson for adult ages, to estimate death probabilities for ages 75+; Akima, to obtain complete life tables from abridged (10-year) life tables; Fraction, to estimate life tables for each calendar year. ^cLife tables for Algeria in 2000. ^dCampinas SP, Goiânia GO. ^eAtlanta GA, California, Los Angeles CA, San Francisco CA, Colorado, Connecticut, Florida, Hawaii, Idaho, Iowa, Louisiana, Michigan, Detroit MI, Nebraska, New Jersey, New Mexico, New York [State], New York City NY, Rhode Island, Seattle WA, Utah, Wyoming. Life tables reconstructed by race: whites, blacks and all races. Life tables for blacks were not reconstructed for Hawaii, Idaho, New Mexico, Utah, Wyoming. ^fInformation only for registries that were not included in EUROCARE-3¹³. Switzerland: Graubunden-Glarus, St Gall-Appenzell, Valais; UK: England (national), Northern Ireland. ^gAustralian Capital Territory, New South Wales, Northern Territory, Queensland, South Australia, Tasmania, Victoria, Western Australia.

Equivalent details for most of the European participating cancer registries have already been published¹⁴. We used the exponential method to obtain probabilities of death (q_x) from death rates¹⁷; the fraction method to interpolate life tables for each calendar year¹⁴; the Elandt-Johnson method to obtain complete life tables from abridged life tables with 5-year age classes; the Elandt-Johnson method for adult ages to estimate the probability of death at ages 75 and over using the Gompertz distribution^18,19; and the Akima method to obtain complete life tables from abridged life tables with 10-year age classes^19,20. For the USA, the SEER*Stat database allowed us the construction of life tables for both SEER and NPCR registry areas, by calendar year and race²¹. Five-year abridged life tables were estimated from these data, and converted to complete life tables with the Elandt-Johnson method. We constructed complete life tables for whites and for all races combined for all 22 cancer registry areas and for blacks in 17 of the 22 areas (Table 1). We could not construct robust life tables for blacks in the states of Hawaii, Idaho, New Mexico, Utah and Wyoming, because the populations were too small.

(b) In the CONCORD study, anonymized individual tumor records on cancer patients diagnosed during 1990-1994 and followed up to 31 December 1999 were supplied to agreed standards by the cancer registries, then subjected to uniform quality control and analyzed centrally⁸. For the present paper, only the US individual data were used. The present analyses aimed to compare relative survival estimates with different life table approaches. The SEER*Stat software³ was used to compare relative survival estimated with the Hakulinen method¹⁰. We used (A) the US race-specific census life tables for 1990 and 2000 applied to the periods 1990-1995 and 1996-1999 respectively (thus following the SEER approach), and (B) the life tables constructed for CONCORD for the period 1990-1999, specific for cancer registry area, single calendar year and race (CONCORD approach) (Table 2). Thus for example, with the SEER approach, the general population probability of survival of a black male cancer patient resident in Los Angeles in 1995 will be the survival probability of a black male of the same age in the USA in 1990, whereas it will be the survival probability of a black male of the same age resident in Los Angeles in 1995 using the CONCORD approach. We compared raw (not age-standardized) estimates of relative survival obtained with the two sets of life tables. We present the absolute differences between survival estimates, e.g., 15% is shown as 5% (not 50%) higher than 10%. Logarithmic transformation was used to estimate normal confidence intervals of the relative survival estimates².

Table 2 - Characteristics of life tables used for relative survival estimates in US cancer registries participating in the CONCORD study

Approach	Life table characteristics

	Age	Sex	Area	Year(s)	Race

SEER	Single year of age	Male	USA (national)	1990 (for years 1990, … 1995)	White,
		Female		2000 (for years 1996 ,… 1999)	Black,
					All races*

CONCORD	Single year of age	Male	Registry area	1990, 1991, … 1999	White,
		Female			Black,
					All races*

*The “all-races” life tables were used for cancer patients who were not of white or black race; or of unknown race; or of black race in Hawaii, Idaho, New Mexico, Utah and Wyoming.

Results

Life expectancy at birth following the CONCORD
approach

Average life expectancy during the decade 1990-99 in the 101 cancer registry populations participating in the CONCORD study varied from 63.7 years for males in Estonia to 77.6 years for males in Japan, a range of 13.9 years (Table 3). For females, the range was from 70.9 years in Algeria to 83.7 years in Japan, a difference of 12.8 years. The median life expectancy among these populations was 74.2 years for men and 80.3 years for women. Life expectancy was below this median in all US black populations, in Cuba, Brazil and Algeria, and in all Eastern European areas (Table 3). The range of life expectancy in Canada and in US white populations was similar to that in northern and western Europe (Figure 1). Average life expectancy during the decade 1990-1999 was always lower in US blacks than in US whites (Figure 1).

Life expectancy increased in almost all countries and regions during the decade 1990-1999. Figure 2 shows average life expectancy during 1990-1994 (x-axis) against the average life expectancy during 1995-1999 (y-axis) for each population (specific by registry area and race) and both sexes. Most points are above the bisection. Life expectancy increased more in men than in women, and more in populations where life expectancy was low during 1990-1994. The largest increases for life expectancy at birth between 1990-1994 and 1995-1999 were seen in the black population of New York City: +4.8 years in males and +2.3 years in females (Table 3).

Table 3 - Life tables constructed for CONCORD study: average life expectancy at birth (years) and difference (years) in life expectancy at birth between 1995-1999 and 1990-1994

Cancer registry^a	Country	World region	Male		Female

			1990-1999	Difference^b	1990-1999	Difference^b

Fukui	Japan	Asia	77.6	+0.6	83.7	+0.9
Yamagata	Japan	Asia	77.0	+0.9	83.1	+1.2
Iceland	Iceland	Northern Europe	76.6	+0.3	80.8	+0.6
Sweden	Sweden	Northern Europe	76.5	+1.3	81.7	+0.9
Australian Capital Territory	Australia	Oceania	76.5	+1.0	81.3	0.0
Macerata	Italy	Western Europe	76.4	+1.1	82.2	+0.8
Tuscany	Italy	Western Europe	76.4	+1.1	82.2	+0.8
Osaka	Japan	Asia	76.3	+1.1	82.5	+1.4
Geneva	Switzerland	Western Europe	76.1	+1.9	82.6	+0.8
Romagna	Italy	Western Europe	76.1	+1.2	82.3	+0.7
Ragusa	Italy	Western Europe	75.9	+0.7	80.4	+0.9
British Columbia	Canada	Canada	75.9	+1.0	81.6	+0.6
Utah (White)	USA	USA-White	75.9	+0.7	80.9	-0.1
Western Australia	Australia	Oceania	75.7	+1.0	81.4	+0.9
Victoria	Australia	Oceania	75.7	+1.4	81.2	+1.0
Navarra	Spain	Western Europe	75.6	+0.6	82.6	+0.9
Basel	Switzerland	Western Europe	75.6	+1.5	81.5	+1.0
South & West	UK	Northern Europe	75.5	+1.1	80.4	+0.8
East Anglia & Oxford	UK	Northern Europe	75.5	+1.0	80.0	+0.7
Ontario	Canada	Canada	75.5	+1.1	81.0	+0.5
South Australia	Australia	Oceania	75.5	+1.4	81.3	+1.1
Tarragona	Spain	Western Europe	75.3	+1.6	81.4	+1.1
Modena	Italy	Western Europe	75.2	+0.8	81.6	+0.8
Grisons-Glaris	Switzerland	Western Europe	75.2	+1.5	81.9	+1.1
St Gall	Switzerland	Western Europe	75.2	+1.3	81.6	+0.6
Saskatchewan	Canada	Canada	75.2	+0.3	81.4	-0.1
Connecticut (White)	USA	USA-White	75.2	+1.0	80.8	+0.2
Tyrol	Austria	Western Europe	75.1	+1.3	80.9	+1.1
Queensland	Australia	Oceania	75.1	+1.2	81.0	+0.9
New South Wales	Australia	Oceania	75.1	+1.6	81.0	+1.2
Amsterdam	Netherlands	Western Europe	75.1	+0.8	80.8	+0.3
South Thames	UK	Northern Europe	75.1	+1.1	80.0	+0.7
Seattle WA (White)	USA	USA-White	75.0	+1.1	80.5	+0.1
Latina	Italy	Western Europe	74.9	+1.1	81.3	+1.1
Parma	Italy	Western Europe	74.9	+1.2	81.8	+1.4
Idaho (White)	USA	USA-White	74.9	+0.8	80.5	+0.4
Torino	Italy	Western Europe	74.9	+1.5	81.2	+1.4
Iowa (White)	USA	USA-White	74.9	+0.8	80.9	0.0
Colorado (White)	USA	USA-White	74.9	+1.2	80.5	+0.1
North Netherlands	Netherlands	Western Europe	74.8	+0.6	80.7	+0.2
Sassari	Italy	Western Europe	74.8	+1.0	81.4	+0.9
Cote d’Or	France	Western Europe	74.7	+1.3	82.6	+1.0
Norway	Norway	Northern Europe	74.7	+1.2	80.6	+0.7
Nebraska (White)	USA	USA-White	74.7	+0.9	80.9	+0.1
Veneto	Italy	Western Europe	74.7	+1.3	81.8	+1.0
Manitoba	Canada	Canada	74.6	+0.6	80.3	-0.2
Isère	France	Western Europe	74.6	+1.2	82.4	+1.0
Nova Scotia	Canada	Canada	74.6	+0.8	80.6	+0.1
Hawaii (White)	USA	USA-White	74.5	+0.6	80.8	+1.1
Rhode Island (White)	USA	USA-White	74.5	+1.1	80.7	+0.7
New Jersey (White)	USA	USA-White	74.4	+1.3	80.1	+0.5
Malta	Malta	Western Europe	74.4	+0.9	79.1	+1.5
Valais	Switzerland	Western Europe	74.3	+1.8	81.7	+0.9
Varese	Italy	Western Europe	74.3	+1.8	81.6	+1.1
Tasmania	Australia	Oceania	74.3	+1.9	80.0	+1.0
Genova	Italy	Western Europe	74.3	+1.6	81.1	+1.3
Florida (White)	USA	USA-White	74.2	+1.2	80.9	+0.2
Murcia	Spain	Western Europe	74.2	+0.8	80.3	+0.7
England	UK	Northern Europe	74.2	+1.2	79.4	+0.8
Trent	UK	Northern Europe	74.2	+1.0	79.2	+0.8
Atlanta GA (White)	USA	USA-White	74.2	+1.6	80.3	+0.1
Michigan (White)	USA	USA-White	74.1	+1.0	79.7	+0.3
Ferrara	Italy	Western Europe	74.1	+0.9	81.0	+1.3
Wyoming (White)	USA	USA-White	74.0	+0.5	79.8	+0.2
West Midlands	UK	Northern Europe	74.0	+1.0	79.0	+0.9
Detroit MI (White)	USA	USA-White	74.0	+1.1	79.6	+0.4
California (White)	USA	USA-White	73.9	+1.7	80.0	+0.5
Eindhoven	Netherlands	Western Europe	73.9	+0.7	79.7	+0.6
Wales	UK	Northern Europe	73.9	+0.8	79.0	+0.5
San Francisco CA (White)	USA	USA-White	73.9	+2.6	80.5	+0.7
Granada	Spain	Western Europe	73.8	+0.7	80.5	+0.7
New Mexico (White)	USA	USA-White	73.7	+0.9	80.2	+0.4
Basque Country	Spain	Western Europe	73.6	+1.0	82.0	+0.8
New York State (White)	USA	USA-White	73.5	+2.1	79.8	+0.8
Mallorca	Spain	Western Europe	73.5	+1.2	81.2	+1.4
Northern Yorkshire	UK	Northern Europe	73.5	+1.1	78.5	+0.9
Los Angeles CA (White)	USA	USA-White	73.4	+2.1	79.9	+0.8
Calvados	France	Western Europe	73.2	+1.3	82.1	+1.0
Northern Ireland	UK	Northern Europe	73.2	+1.0	78.8	+0.6
Cuba	Cuba	South and Central America	73.1	+0.8	77.0	+1.1
Mersey and North Western	UK	Northern Europe	73.0	+0.9	78.2	+0.7
Bas-Rhin	France	Western Europe	73.0	+1.2	81.0	+0.8
Denmark	Denmark	Northern Europe	73.0	+1.0	78.2	+0.6
Ireland	Ireland	Northern Europe	72.9	+0.9	78.4	+0.8
Saarland	Germany	Western Europe	72.6	+1.2	78.9	+0.9
Finland	Finland	Northern Europe	72.5	+1.3	80.0	+1.0
Louisiana (White)	USA	USA-White	72.2	+1.1	78.8	+0.1
Scotland	UK	Northern Europe	72.0	+0.8	77.5	+0.7
Portugal	Portugal	Western Europe	71.3	+0.4	78.5	+0.5
New York City NY (White)	USA	USA-White	71.1	+3.6	79.0	+1.3
Slovenia	Slovenia	Western Europe	70.4	+1.6	78.1	+1.2
Colorado (Black)	USA	USA-Black	70.1	+2.5	76.3	-0.1
Cracow	Poland	Eastern Europe	69.7	+1.6	76.8	+0.8
Seattle WA (Black)	USA	USA-Black	69.6	+1.9	76.5	+0.5
West Bohemia	Czech Rep	Eastern Europe	69.6	+2.1	76.1	+1.5
Northern Territory	Australia	Oceania	69.0	+2.3	74.2	+2.3
Rhode Island (Black)	USA	USA-Black	69.0	+4.1	75.4	+1.2
Warsaw	Poland	Eastern Europe	68.9	+1.3	76.8	+0.6
Slovakia	Slovakia	Eastern Europe	68.1	+1.2	76.3	+0.7
Iowa (Black)	USA	USA-Black	67.7	+0.7	75.1	-0.4
Connecticut (Black)	USA	USA-Black	67.4	+3.1	76.2	+0.6
Nebraska (Black)	USA	USA-Black	67.1	+1.1	73.6	-1.4
Setif^c	Algeria	Africa	67.1	-	70.9	-
California (Black)	USA	USA-Black	67.1	+2.6	74.8	+0.9
New York State (Black)	USA	USA-Black	67.1	+4.3	75.8	+2.0
Goiania	Brasil	South and Central America	67.0	+0.3	75.5	+0.6
Campinas	Brasil	South and Central America	66.6	-0.2	76.6	+1.0
New York City NY (Black)	USA	USA-Black	66.6	+4.8	76.0	+2.3
Florida (Black)	USA	USA-Black	66.3	+2.5	74.2	+1.2
Atlanta GA (Black)	USA	USA-Black	65.7	+2.4	74.7	+1.1
New Jersey (Black)	USA	USA-Black	65.7	+3.1	73.9	+1.1
Los Angeles CA (Black)	USA	USA-Black	65.7	+3.0	74.6	+1.0
San Francisco CA (Black)	USA	USA-Black	65.2	+2.7	74.6	+0.6
Michigan (Black)	USA	USA-Black	65.0	+1.9	73.6	+0.7
Louisiana (Black)	USA	USA-Black	64.8	+1.6	73.7	+0.3
Detroit MI (Black)	USA	USA-Black	64.0	+2.2	73.3	+0.5
Estonia	Estonia	Eastern Europe	63.7	+0.9	74.8	+1.3

^aRanked by male life expectancy in 1990-1999. ^bDifferences between average life expectancy at birth in 1995-1999 and 1990-1994. ^cOne life table used for all calendar years.

Comparing CONCORD and SEER approaches

Life expectancy in the SEER approach was fixed for all 22 populations (71.8 years and 74.1 years in males respectively for 1990 and 2000; 78.8 years and 79.5 years in females respectively for 1990 and 2000) because it was derived from the overall US census national life table in 1990 and 2000. Average life expectancy in most of the US states and metropolitan cancer registry areas participating in CONCORD for the periods 1990-1995 and 1996-1999 was greater than or similar to the US census life expectancy respectively for 1990 and 2000 (Table 4). Louisiana, Detroit (MI), Atlanta (GA) and New York City (NY) were the only areas in which life expectancy was lower than the US census life expectancy both for males and females for both periods: major differences were in Louisiana. In contrast, the highest average life expectancy was always in Hawaii: 4.0 years higher for males and 3.2 years higher for females during 1990-1995 than the US census life expectancy for 1990, and 2.5 years higher for males and 3.0 years for females during 1996-1999 than the US census life expectancy for 2000. Life expectancy in the USA increased between 1990-1995 and 1996-1999 in all areas for males and in most areas for females (Table 4).

Table 4 - Life expectancy at birth in the USA, derived from CONCORD life tables and differences (in years) with life expectancy at birth derived from US Census life tables, all races

CONCORD US Area^a	Male				Female
	CONCORD	Difference	CONCORD	Difference	CONCORD	Difference	CONCORD	Difference
		from US		from US		from US		from US
		Census^b		Census^c		Census^d		Census^e
	1990-1995	1990	1996-1999	2000	1990-1995	1990	1996-1999	2000

Louisiana	69.5	-2.3	70.8	-3.3	77.2	-1.6	77.4	-2.1
Detroit MI	71.0	-0.8	72.4	-1.7	77.8	-1.0	78.3	-1.2
Atlanta GA	71.1	-0.7	72.9	-1.2	78.5	-0.3	78.9	-0.6
New York City NY	68.8	-3.0	73.0	-1.1	77.7	-1.1	79.4	-0.1
Michigan	72.3	+0.5	73.5	-0.6	78.7	-0.1	79.0	-0.5
New Mexico	72.9	+1.1	74.0	-0.1	79.8	+1.0	80.3	+0.8
Florida	72.7	+0.9	74.3	+0.2	79.9	+1.1	80.3	+0.8
Wyoming	73.5	+1.7	74.3	+0.2	79.6	+0.8	79.6	+0.1
New York State	71.6	-0.2	74.4	+0.3	78.8	0.0	79.9	+0.4
New Jersey	72.7	+0.9	74.5	+0.4	79.0	+0.2	79.8	+0.3
Los Angeles CA	72.3	+0.5	74.7	+0.6	79.4	+0.6	80.2	+0.7
Nebraska	74.1	+2.3	74.9	+0.8	80.6	+1.8	80.6	+1.1
Rhode Island	73.7	+1.9	75.1	+1.0	80.2	+1.4	80.9	+1.4
California	73.1	+1.3	75.1	+1.0	79.8	+1.0	80.3	+0.8
Idaho	74.5	+2.7	75.3	+1.2	80.3	+1.5	80.8	+1.3
Iowa	74.4	+2.6	75.3	+1.2	80.8	+2.0	80.9	+1.4
Connecticut	74.0	+2.2	75.3	+1.2	80.3	+1.5	80.7	+1.2
San Francisco CA	72.5	+0.7	75.4	+1.3	80.1	+1.3	80.9	+1.4
Colorado	74.2	+2.4	75.6	+1.5	80.4	+1.6	80.4	+0.9
Seattle WA	74.5	+2.7	75.7	+1.6	80.4	+1.6	80.6	+1.1
Utah	75.5	+3.7	76.2	+2.1	80.8	+2.0	80.9	+1.4
Hawaii	75.8	+4.0	76.6	+2.5	82.0	+3.2	82.5	+3.0

^aRanked by average male life expectancy during 1996-99 column. ^bUS Census life expectancy at birth in males for 1990 was 71.8 years. ^cUS Census life expectancy at birth in males for 2000 was 74.1 years. ^dUS Census life expectancy at birth in females for 1990 was 78.8 years. ^eUS Census life expectancy at birth in females for 2000 was 79.5 years.

The variation in all-cause mortality by time and place affects the international comparability of relative survival estimates. In the USA, relative survival estimates derived using the CONCORD approach to the deployment of life tables were systematically lower than those derived with the SEER approach to life tables (taken as the reference values) (Table 5). The only exception was Louisiana. The differences in colorectal cancer survival were generally greater for men. The largest differences were seen in Hawaii, where general population mortality is considerably lower than the US national average. For Hawaii, the absolute difference in relative survival was -1.6% for breast cancer in women, -3.3% and -2.1% for males and females, respectively, for colorectal cancer, and -5.7% for prostate cancer.

For each cancer, the CONCORD estimate of relative survival at five years in all registries combined fell below the 95% confidence interval for the SEER estimate (Table 5).

Discussion

The CONCORD study was originally designed to compare relative survival from cancer in the USA (including cancer registries participating in either the SEER or NPCR Programs) and Europe, using a single methodological approach. Relative survival is the ratio between the observed probability of survival in the cancer patients and the expected probability of survival based on general population mortality. A key difference exists, however, between the USA (SEER) and Europe (EUROCARE) in how life tables are used in the estimation of relative survival. To avoid problems of this type, the CONCORD study constructed complete life tables that were specific for sex, cancer registry area, calendar year and, where possible, race. These life tables reflect the wide variations in mortality between and within the participating 101 populations and the systematic increases in life expectancy with time during the decade 1990-1999.

We used this approach also in the USA because we expected for most areas that US relative survival estimates based on life tables by cancer registry area and calendar year (CONCORD approach) would be lower than those based on US census national life tables (i.e., US life table in 1990 for the years 1990-1995 and US life tables in 2000 for 1996-1999). This is because most CONCORD cancer registry areas in 1990-1995 and 1996-1999 had higher life expectancy than the USA in 1990 and 2000, that is higher expected survival than for the USA as a whole in census years. Relative survival under this approach thus reflects the survival of the cancer patients relative to that of the general population of that sex and race and in that place and time.

Relative survival estimates were, in fact, lower with the CONCORD approach than with the SEER approach. The single exception was Louisiana, where average life expectancy was lower than that of the US national population. Differences in relative survival between the SEER and CONCORD approaches were greater for men than for women, because general population mortality in participating areas of the USA during the decade 1990-1999 varied more widely from the US national mortality in males than it did for females. Differences in the survival estimates between the two approaches were always greatest in Hawaii, because general population mortality differed more widely from the US national average mortality in that state than elsewhere.

The analysis of the role of life tables in relative survival for different cancer sites is a complex matter. Under the hypothesis of invariability of expected survival ES₁ and ES₂, differences between two relative survival estimates obtained with different life tables

will increase with increasing prognosis (that is, with increasing observed survival, OS). In our database, the patient age distribution was similar for prostate and colorectal cancer in men but not for breast and colorectal cancer in women. This means that prostate cancer patients and male colorectal cancer patients had similar expected survivals (ES₁ estimated with US census life tables and ES₂ estimated with CONCORD life tables). Consequently, we expected larger differences

in relative survival using different life tables for prostate cancer than for colorectal cancer in men, because prostate cancer has a better prognosis (as can be seen in Table 5).

Possible limits of the CONCORD approach regard principally the instability of estimated life table for small populations, which can affect the standard errors of the relative survival estimates. To avoid these problems, three-year moving averages of expected survival can be used instead of life tables for single calendar years. The CONCORD life tables do not include socio-economic status among the sources of variation in background mortality, because few countries have adequate population mortality data for this purpose²².

In conclusion, for international comparisons of cancer survival, it is important to use standard methods in order to provide policy-makers with robust and comparable information for cancer control. After analyzing secular trends and global variations in all-cause mortality and variations by race in some countries, we suggest that relative survival estimates for international comparison should, if possible, be based on stable, complete (single year-of-age) life tables that capture background mortality in the area (country, region, city) where the cancer patients live by sex, single calendar year and race.

CONCORD Working Group

Africa Algeria: M Hamdi Chérif (Sétif Cancer Registry, Sétif).

America, Central and South Brazil: N Mahayri, DC Moreira Filho (Cancer Registry of Campinas, Campinas SP); MP Curado (Cancer Registry of Goiânia, Goiás GO); S Koifman* (National School of Public Health, Rio de Janeiro); G Azevedo e Silva* (Rio de Janeiro State University); Cuba: L Fernandes Garrote (National Cancer Registry, Havana).

America, North Canada: AJ Coldman, M McBride (British Columbia Cancer Registry, Vancouver); A Demers*, E Kliewer, D Turner (Manitoba Cancer Registry, Winnipeg); R Dewar (Nova Scotia Cancer Registry, Halifax); E Holowaty, L Marrett, D Mishri (Ontario Cancer Registry, Toronto); J Tonita (Saskatchewan Cancer Registry, Saskatchewan); J Hatcher, Y Mao (Health Canada, Ottawa); A-M Ugnat, C Waters (Case Surveillance Division, Ottawa); USA: JL Young* (Metro Atlanta Cancer Registry, Atlanta GA); HK Weir* (Centers for Disease Control and Prevention, Atlanta GA); WE Wright, D Yin (California State Cancer Registry, Sacramento CA); D Deapen (Los Angeles County Cancer Surveillance Program, Los Angeles CA); D West (Greater Bay Area Cancer Registry, San Francisco CA); K Bol, R Bott, J Finch (Colorado Central Cancer Registry, Denver CO); A Polednak (Connecticut Tumor Registry, Hartford CT); J MacKinnon (Florida Tumor Registry, Miami FL); MT Goodman (Hawaii Tumor Registry, Honolulu HI); S Carson, C Johnson (Cancer Data Registry of Idaho, Boise ID); CF Lynch (State Health Registry of Iowa, Iowa City IO); V Chen (Louisiana Tumor Registry, New Orleans LA); G Copeland (Michigan Tumor Registry, Lansing MI); J Graff (Metropolitan Detroit Cancer Surveillance System, Detroit MI); V Filos, S Frederick (Nebraska Cancer Registry, Lincoln NE); B Kohler (New Jersey State Cancer Registry, Trenton NJ); C Wiggins (New Mexico Tumor Registry, Albuquerque NM); CC McLaughlin, MJ Schymura (New York State Cancer Registry, Albany NY); J Fulton, D Rousseau (Rhode Island Cancer Registry, Providence RI); M Potts, S Schwartz (Cancer Surveillance System of Western Washington, Seattle WA): R Dibble, N Stroup (Utah Cancer Registry, Salt Lake City UT); J Brockhouse, J Grandpré (Wyoming Cancer Surveillance Program, Cheyenne WY).

Asia Japan: M Fujita (Fukui Cancer Registry, Fukui); W Ajiki, H Tsukuma* (Osaka Cancer Registry, Osaka); T Matsuda (Yamagata Cancer Registry, Yamagata).

Europe Austria: W Oberaigner (Tyrol Cancer Registry, Innsbruck); Czech Republic: J Holub (West Bohemia Cancer Registry, Prague); Denmark: HH Storm (Danish Cancer Society, Department of Cancer Prevention and Documentation, Copenhagen); Estonia: T Aareleid, M Rahu (Estonian Cancer Registry, Tallinn); Finland: T Hakulinen* (Finnish Cancer Registry, Helsinki); France: G Hédelin, M Velten (Bas-Rhin Cancer Registry, Strasbourg); G Launoy, J Macé-Lesech (Calvados Digestive Cancer Registry, Caen); G Chaplain (Côte d'Or Gynaecologic Registry, Dijon), J Faivre (Côte d'Or Digestive Tract Registry, Dijon); M Colonna (Isère Cancer Registry, Meylan); Germany: H Ziegler (Saarland Cancer Registry, Saarbrucken); Iceland: L Tryggvadóttir (Icelandic Cancer Registry, Reykjavik); Ireland: H Comber (National Cancer Registry of Ireland, Cork); Italy: S Ferretti (Ferrara Cancer Registry, Ferrara); M Vercelli (Liguria Cancer Registry, Genova); F Albertoni, E Conti, F Pannozzo (Latina Cancer Registry, Rome); F Pannelli, S Vitarelli (Macerata Cancer Registry, Camerino); C Allemani, P Baili, F Berrino*, L Ciccolallo, G Gatta*, A Micheli*, M Sant* (National Cancer Institute, Milan); ME Artioli, M Federico, M Ponz de Leon (Modena Cancer Registry, Modena); V De Lisi, L Serventi (Parma Cancer Registry, Parma); L Gafà, R Tumino (Ragusa Cancer Registry, Ragusa); F Falcini (Romagna Cancer Registry, Forlì); R Capocaccia*, R De Angelis, S Francisci, M Santaquilani, A Verdecchia* (Istituto Superiore di Sanità, Rome); M Budroni, R Cesaraccio (Sassari Cancer Registry, Sassari); S Patriarca, R Zanetti (Torino Cancer Registry, Torino); E Crocetti, E Paci (Tuscany Cancer Registry, Firenze); P Contiero, P Crosignani, G Tagliabue (Lombardy Cancer Registry, Varese); S Guzzinati, P Zambon (Venetian Cancer Registry, Padova); Malta: M Dalmas (Malta National Cancer Registry, Valletta); Netherlands: O Visser (Amsterdam Cancer Registry, Amsterdam); R Otter, M Schaapveld (North Netherlands Cancer Registry, Groningen); JW Coebergh (South Netherlands Cancer Registry, Eindhoven); Norway: A Andersen, F Langmark (Cancer Registry of Norway, Oslo); Poland: J Rachtan (Krakow Cancer Registry, Krakow); M Bielska-Lasota, Z Wronkoski, M Zwierko (Warsaw Cancer Registry, Warsaw); Portugal: AM da Costa Miranda (Southern Portugal Cancer Registry, Lisbon); Slovakia: M Ob sˇitniková, I Plesˇko (National Cancer Registry of Slovakia, Bratislava); Slovenia: V Pompe-Kirn, M Primic-Zˇakelj (Cancer Registry of Slovenia, Ljubljana); Spain: I Izarzugaza (Basque Country Cancer Registry, Vitoria-Gasteiz); C Martinez Garcia, MJ Sánchez-Pérez (Granada Cancer Registry, Granada); I Garau (Mallorca Cancer Registry, Palma de Mallorca); MD Chirlaque, C Navarro Sanchez (Murcia Cancer Registry, Murcia); E Ardanaz, C Moreno (Navarra Cancer Registry, Pamplona); J Galceran (Tarragona Cancer Registry, Reus); Sweden: TA Alvegård, L Barlow (Cancer Registry of Sweden, Stockholm); Switzerland: G Jundt (Basel Cancer Registry, Basel); J-M Lutz*, M Ussel (Geneva Cancer Registry, Geneva); H Frick (Graubunden-Glarus Cancer Registry, Chur); S Ess (St Gallen-Appenzell Cancer Registry, St Gallen); I Konzelmann (Valais Cancer Registry, Sion); UK - England: T Davies, S Godward, J Rashbass (Eastern Cancer Registration and Information Centre, Cambridge); N Cooper, MJ Quinn (National Cancer Registry, Office for National Statistics, London); MP Coleman*, M Quaresma, B Rachet (London School of Hygiene and Tropical Medicine, London); L Shack, EMI Williams (Merseyside and Cheshire Cancer Registry, Liverpool): M Roche (Oxford Cancer Intelligence Unit, Oxford); H Møller (South Thames Cancer Registry, London); J Smith, J Verne (South West Cancer Intelligence Service, Bristol); H Botha, D Meechan (Trent Cancer Registry, Sheffield); G Lawrence (West Midlands Cancer Intelligence Unit, Birmingham); D Forman (Northern and Yorkshire Cancer Registry and Information Service, Leeds); UK - Northern Ireland: A Gavin (Northern Ireland Cancer Registry, Belfast); UK - Scotland: R Black, DH Brewster (Scottish Cancer Intelligence Unit, Edinburgh); UK - Wales: J Steward (Welsh Cancer Intelligence and Surveillance Unit, Cardiff).

Oceania Australia: JM Elwood* (Australian Capital Territory Cancer Registry, Canberra); F Sitas (New South Wales Central Cancer Registry, Sydney); J Condon (Northern Territory Cancer Registry, Casuarina); J Aitken (Queensland Cancer Registry, Brisbane); David Roder (South Australian Cancer Registry, Adelaide); A Venn (Tasmanian Cancer Registry, Hobart); G Giles* (Victorian Cancer Registry, Carlton); T Threlfall (Western Australian Cancer Registry, East Perth).

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