How Effective is Population-Based Cancer Screening? Regression Discontinuity Estimates from the US Guideline Screening Initiation Ages

Srikanth Kadiyala; Erin Strumpf

doi:10.1515/fhep-2014-0014

Article

How Effective is Population-Based Cancer Screening? Regression Discontinuity Estimates from the US Guideline Screening Initiation Ages

Srikanth Kadiyala and Erin Strumpf

Published/Copyright: January 28, 2016

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From the journal Forum for Health Economics and Policy Volume 19 Issue 1

Abstract

We estimate the marginal benefits of population-based cancer screening by comparing cancer test and detection rates on either side of US guideline-recommended initiation ages (age 40 for breast cancer and age 50 for colorectal cancer during the study period). Using a regression discontinuity design and self-reported test data from national health surveys, we find test rates for breast and colorectal cancer increase at the guideline age thresholds by 109% and 78%, respectively. Data from cancer registries in twelve US states indicate that cancer detection rates increase at the same thresholds by 50% and 49%, respectively. We estimate significant effects of screening on earlier breast cancer detection (1.2 cases/1000 screened) at age 40 and colorectal cancer detection (1.1 cases/1000 individuals screened) at age 50. Forty-eight and 73% of the increases in breast and colorectal case detection occur among middle-stage cancers (localized and regional) with most of the remainder among early-stage (in-situ). Our analysis suggests that the cost of detecting an asymptomatic case of breast cancer at age 40 via population-based screening is $107,000–134,000 and that the cost of detecting an asymptomatic case of colorectal cancer at age 50 is $473,000–485,000.

Keywords: cancer detection; cancer screening; regression discontinuity design

JEL: I10; I12; I18

Corresponding author: Erin Strumpf, McGill University, Department of Economics and Department of Epidemiology, Biostatistics and Occupational Health, 855 Sherbrooke St. West, Montreal, Quebec H3A 2T7, Canada, e-mail: erin.strumpf@mcgill.ca

Acknowledgments

We thank Michael Anderson, Marianne Bitler, Tom Chang, David Cutler, Christopher Carpenter, Ruth Etzioni, Eduardo Franco, Roman Gulati, James Hanley, Sam Harper, Jay Kaufman, Sendhil Mullainathan, Carolyn Rutter, 4 anonymous referees, the editor and participants in several seminars for helpful comments, and Zhijin Chai and Sam Masters for excellent research assistance. Erin Strumpf was supported by a Chercheur Boursier Junior 1 from the Fonds de la Recherche du Québec-Santé and the Ministère de la Santé et des Services sociaux du Québec.

Appendix 1: Additional Mortality Analyses

US Mortality Data (Vital Statistics 2000–2006)

Figures A1 and A2 plot age-specific breast and colorectal cancer mortality rates, respectively, compared with predicted mortality rates based on ages where guidelines were not in effect. We ran a linear regression of log mortality on age for ages at which the higher screening rates should not affect mortality (ages 40–44 for breast cancer, ages 45–49 for colorectal) and used the resulting coefficients to predict age-specific mortality at all ages. As expected, there are no visually identifiable discontinuities in observed breast cancer mortality at age 40 or colorectal cancer mortality at age 50, but we see a clear divergence between the actual and predicted breast cancer mortality rates. For 5-year age groups, we flexibly test to see if the relative cancer mortality rate differs from the predicted relative rate using the following regression model:

Figure A1:

Observed vs. predicted breast cancer mortality rates, by age.

Figure A2:

Observed vs. predicted colorectal cancer mortality rates, by age.

(6)Ln(Mortay)=λ0+λ1AgeGroupay+λ2Observeday+λ3AgeGroupay∗Observeday+uay (6)

where the dependent variable is the log of the age-cancer-specific mortality rate, AgeGroup is a set of 5-year age group indicators, and Observed is an indicator for observed data. The set of λ₃ parameters indicates whether the relative mortality rates in the observed data are statistically different from the predicted values.

Columns a and b in Table A1 present results for breast and colorectal cancer mortality. Beginning at ages 50–54, about 10 years after the sharp increase in screening rates, we observe that breast cancer mortality rates relative to ages 40–44 are significantly lower in the observed data than the predicted. The gap remains statistically significant and grows in magnitude as age increases. Similarly, beginning at ages 55–59, about 5 years after the sharp increase in colorectal cancer screening rates, mortality rates relative to ages 45–49 are significantly lower in the observed data than what we predicted. This evidence supports the hypothesis that the discontinuous increase in screening rates for breast and colorectal cancer impact mortality. Specifically, we observe a significant decrease in the growth of the mortality rate that increases with age and does not appear contemporaneously with the change in screening rates, but rather after a sufficient lag to allow screening to causally impact mortality.

Table A1

Relative Cancer Mortality.

	US observed mortality vs. Predicted mortality			US observed mortality vs. Canadian observed mortality
	Breast cancer	Colorectal cancer		Breast cancer	Colorectal cancer
	a	b	c	d
30–34	–1.0602***	–2.0637***
	0.0447	0.0558
35–39	–0.5301***	–1.3758***	35–39	–0.6426***	–1.3680***
	0.0447	0.0558		0.0407	0.0485
40–44	Ref	–0.6879***	40–44	Ref	–0.6947***
		0.0558			0.0485
45–49	0.5301***	Ref	45–49	0.4797***	Ref
	0.0447			0.0407
50–54	1.0602***	0.6879***	50–54	0.9020***	0.6008***
	0.0447	0.0558		0.0407	0.0485
55–59	1.5904***	1.3758***	55–59	1.2129***	1.1172***
	0.0447	0.0558		0.0407	0.0485
60–64	2.1205***	2.0637***	60–64	1.4349***	1.6055***
	0.0447	0.0558		0.0407	0.0485
65–69	2.6506***	2.7516***	65–69	1.6031***	2.0267***
	0.0447	0.0558		0.0407	0.0485
70–74	3.1807***	3.4395***	70–74	1.8038***	2.3882***
	0.0447	0.0558		0.0407	0.0485
75+	4.0289***	4.5402***	75+	2.0032***	2.7188***
	0.0381	0.0476		0.0407	0.0485
Observed	0.0000	0.0014	Canada	–0.1236**	–0.1037*
	0.0447	0.0558		0.0407	0.0485
30–34*obs	–0.5055***	–0.0020
	0.0632	0.0789
35–39*obs	–0.1075	0.0128	35–39*Can	0.0476	–0.1223
	0.0632	0.0789		0.0575	0.0686
40–44*obs	Ref	–0.0027	40–44*Can	Ref	–0.1469*
		0.0789			0.0686
45–49*obs	–0.0450	ref	45–49*Can	0.1061	ref
	0.0632			0.0575
50–54*obs	–0.1592*	–0.090	50–54*Can	0.1887***	0.1157
	0.0632	0.079		0.0575	0.0686
55–59*obs	–0.3709***	–0.2658***	55–59*Can	0.1157*	0.2447***
	0.0632	0.0789		0.0575	0.0686
60–64*obs	–0.6720***	–0.4674***	60–64*Can	0.2113***	0.2425***
	0.0632	0.0789		0.0575	0.0686
65–69*obs	–1.0397***	–0.7356***	65–69*Can	0.1701**	0.2655***
	0.0632	0.0789		0.0575	0.0686
70–74*obs	–1.3718***	–1.0636***	70–74*Can	0.1832**	0.2667***
	0.0632	0.0789		0.0575	0.0686
75+*obs	–1.8748***	–1.6154***	75+*Can	0.2143***	0.3080***
	0.0539	0.0673		0.0575	0.0686
Constant	2.7163***	2.0252***	Constant	2.7341***	2.0324***
	0.0316	0.0394		0.0288	0.0343
N	784	784	N	540	540

Predicted mortality calculated using a linear model based on ages 40–44 for breast cancer and ages 45–49 for colorectal cancer. Ref=reference group.

Results are robust to adding year fixed effects, year*agegroup and year*canada interactions.

Data source: colum ns a and b – US Vital Statistics 2000–2006 ages 30–85; columns c and d – US and Canadian Vital Statistics 2000–2005 ages 35–79.

US-Canada Comparison of Cancer Mortality

Figures A3 and A4 illustrate log age-specific cancer mortality rates from breast and colorectal cancer in Canada and the US, with only the case of colorectal cancer demonstrating support for our initial hypotheses based on a visual assessment. Estimating the following regression allows us to examine whether the relative mortality rates for various five-year age groups are significantly different in Canada relative to the US, after controlling for fixed differences across countries and shared age trends:

Figure A3:

US vs. Canadian breast cancer mortality rates, by age.

Figure A4:

US vs. Canadian colorectal cancer mortality rates, by age.

(7)Ln(Mortay)=δ0+δ1AgeGroupay+δ2Canadaay+δ3AgeGroupay∗Canadaay+ωay (7)

Column c in Table A1 shows that the relative breast cancer mortality rates in the two countries are similar in the 35–39 and 45–59 age groups, but among the 50–54 year olds Canadian relative mortality is higher than in the US. This supports the hypothesis that screening affects mortality, since the screening rate has been effective for 10 years of age in the US, while the screening rate among Canadian women increases sharply only at age 50 (Strumpf et al. 2010). From ages 55–59, relative mortality rates are closer, which could indicate an impact of the change in Canadian screening patterns at age 50. However, we see that by ages 60 and 70 Canada is not “catching up,” but rather that the relative mortality rate remains significantly higher than in the US. While this could be interpreted as evidence against population-based screening impacting mortality, it could also be the result of differences in treatment conditional on screening and detection. Furthermore, we have documented that, while we do observe a discontinuous increase in mammography rates at the Canadian recommended initiation age of 50, Canadian breast cancer screening rates are close to those observed in the US only for a short span of ages, approximately 55–65 (Kadiyala and Strumpf 2011). Other explanations for the observation that Canadian breast cancer mortality rates remain higher than in the US is that the screening initiation age of 50 is “too late” or that Canadian mammography rates are not high enough over a long enough age range to significantly impact relative mortality.

The results for colorectal cancer in Column d also show support for a mortality effect due to increased screening at age 50. Canadian colorectal cancer screening rates do not exhibit a discontinuity at age 50 and remain 5–10 percentage points below US rates from age 50–80. In ages 40–44, US colorectal cancer mortality is higher than in Canada but mortality rates between the two countries converge soon after. From ages 55 on, about 5 years after the increase in screening at age 50 in the US, we again begin to see a divergence in colorectal cancer mortality patterns between these two countries. Canadian colorectal cancer mortality rates surpass US mortality and are approximately 25% higher than US rates.

Appendix 2: Additional Tables and Figures

Table A2

Covariate Comparison Just Above and Below the Guideline-Recommended Initiation Age.

	Age		p	N
	35–39	41–44	p	N
Breast cancer sample
Non-white	0.403	0.350	0.000	39,153
Less than high school	0.119	0.107	0.132	39,250
High school	0.237	0.260	0.006
Some college	0.272	0.291	0.028
College grad	0.372	0.342	0.001
Income quartile 1	0.131	0.119	0.129	35,607
Income quartile 2	0.149	0.138	0.117
Income quartile 3	0.120	0.121	0.924
Income quartile 4	0.599	0.622	0.027
Married	0.696	0.704	0.387	38,931
Divorced	0.140	0.171	0.000
Never married	0.121	0.084	0.000
Widowed	0.008	0.015	0.000
Couple	0.043	0.031	0.022	29,967
Health insurance	0.841	0.860	0.012	39,322

	Age		p	N
	45–49	51–54	p	N

Colorectal cancer sample
Non-white	0.178	0.165	0.041	18,868
Less than high school	0.120	0.120	0.990	18,635
High school	0.299	0.284	0.063
Some college	0.294	0.304	0.214
College grad	0.290	0.294	0.565
Married	0.680	0.693	0.090	18,771
Divorced	0.158	0.171	0.020
Never married	0.100	0.070	0.000
Widowed	0.015	0.029	0.000
Couple	0.048	0.037	0.003
Health insurance	0.851	0.876	0.000	18,822
Male	0.489	0.494	0.540	18,868

Weighted means to account for survey sample designs. Breast cancer sample: BRFSS 2000, 2002, 2004, 2006, 2008. Colorectal cancer sample: NHIS 2000, 2003, 2005, 2008.

Table A3

Screening Test Use According Risk Factor Characteristics.

	Breast cancer screening: BRFSS data Estimated discontinuity in test rate				Colorectal cancer screening: NHIS data Estimated discontinuity in test rate
	Percent with risk factor at age 39	With risk factor	Without risk factor	Overall average	Percent with risk factor at age	With risk factor	Without risk factor	Overall average
	1	2	3	4	1	2	3	4
Smokes every day	15.1%	18.4 (2.9)	25.3 (1.5)	24 (1.3)	21.0%	2.9 (1.9)	8.5 (1.1)	7.4 (1.0)
Average 2 or more drinks day	3.2%	13.1 (7.4)	25.4 (1.5)	24 (1.3)	5.0%	4.9 (3.7)	7.6 (1.0)	7.4 (1.0)
Average 3 or more drinks day	2.6%	8.8 (8.5)	25.4 (1.5)	24 (1.3)	3.0%	1.6 (4.2)	7.6 (1.0)	7.4 (1.0)
Obese (BMI>30)	24.0%	18.8 (1.5)	21.1 (0.9)	24 (1.3)	32.0%	6.7 (1.2)	8.9 (1.8)	7.4 (1.0)
Self reported health (Good/Fair/Poor)	38.0%	24.9 (2.2)	23.5 (1.7)	24 (1.3)	44.0%	7.1 (1.3)	7.7 (1.6)	7.4 (1.0)
No exercise	19.7%	23.6 (1.6)	26.3 (1.6)	24 (1.3)	65.4%	5.2 (0.014)	8.7 (1.4)	7.4 (1.0)

BRFSS data: SEER states 2000, 2002, 2004, 2006, 2008, except for alcohol use and exercise, where the questions are not asked of everyone in 2000. NHIS data: all states 2000, 2003, 2005, 2008. Individual-level data used in regressions. Standard errors are parentheses and adjust for heteroskedasticity. All regressions drop the GRIA observations (age 40 for brest, 50 for colorectal), include linear age trends on either side of the GRIA, and use a 10-year bandwidth to maximize samples for the low-incidence risk factors. Weighted averages of discontinuities for individuals with and without risk factors (columns 2 and 3) will sum approximately to the figures in column 4. The time frames for questions regarding alcohol use and exercise are the past 30 days in the BRFSS and one year in the NHIS.

Table A4

Breast and Colorectal Cancer Stage Distributions Detected Clinically (1970s) and via Screening (2000s).

Stage distributions	Breast cancer		Colorectal cancer
Stage distributions	1975–1979 (%)	2000–2008 (%)	1975–1979 (%)	2000–2008 (%)
In Situ	6.9	50.2	4.9	20.6
Localized	48.7	37.6	34.2	70.3
Regional	39.4	10.6	38.0	2.3
Distant	5.0	1.6	23.0	6.8

Data: SEER for various years; ages 40–45 for breast cancer and 50–55 for colorectal cancer. 1975–1979 stage distributions reflect clinical detection before screening was widespread. The 2000–2008 distributions reflect cases detected via increased screening at the guideline recommended ages.

Table A5

Stage-Specific Survival Probabilities, 1975–1979.

Years since diagnosis	Breast cancer			Colorectal cancer
Years since diagnosis	Localized	Regional	Distant	In-Situ	Localized	Regional	Distant
1	0.995	0.970	0.698	0.995	0.983	0.918	0.482
2	0.978	0.899	0.496	0.983	0.953	0.784	0.244
3	0.949	0.819	0.373	0.981	0.917	0.678	0.151
4	0.925	0.759	0.299	0.975	0.890	0.609	0.111
5	0.906	0.705	0.235	0.972	0.863	0.569	0.093
6	0.888	0.669	0.205	0.960	0.845	0.537	0.081
7	0.874	0.639	0.189	0.957	0.830	0.516	0.078
8	0.862	0.614	0.179	0.954	0.823	0.506	0.073
9	0.846	0.588	0.159	0.954	0.814	0.501	0.070
10	0.835	0.571	0.152	0.951	0.809	0.496	0.068
11	0.825	0.556	0.137	0.948	0.807	0.490	0.066
12	0.814	0.542	0.127	0.948	0.802	0.486	0.066
13	0.808	0.529	0.119	0.948	0.798	0.484	0.065
14	0.803	0.521	0.119	0.944	0.795	0.480	0.065
15	0.798	0.512	0.119	0.944	0.790	0.477	0.065
16	0.793	0.502	0.119	0.944	0.786	0.475	0.065
17	0.787	0.497	0.119	0.940	0.783	0.473	0.064
18	0.781	0.487	0.115	0.936	0.782	0.471	0.064
19	0.777	0.481	0.108	0.928	0.778	0.469	0.062
20	0.772	0.477	0.104	0.928	0.776	0.469	0.061
21	0.764	0.473	0.104	0.928	0.772	0.468	0.061
22	0.759	0.469	0.104	0.928	0.770	0.466	0.059
23	0.755	0.465	0.104	0.923	0.767	0.463	0.059
24	0.752	0.459	0.104	0.923	0.765	0.461	0.059
25	0.748	0.454	0.104	0.923	0.764	0.458	0.059

Data: US SEER 1975–1979.

We assume 100% survival for breast cancers detected in the in-situ stage.

Figure A5:

Percent of women reporting being married or in a couple, by age.

Figure A6:

Percent of women reporting having graduated college, by age.

Figure A7:

Percent of adults reporting being married or in a couple, by age.

Figure A8:

Percent of adults reporting having graduated college, by age.

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Published Online: 2016-1-28

Published in Print: 2016-6-1

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Articles in the same Issue

https://doi.org/10.1515/fhep-2014-0014

Keywords for this article

cancer detection; cancer screening; regression discontinuity design