A Suitable Approach to Estimate Cancer Incidence in Area without Cancer Registry

Table 2

Cross-validation of breast cancer estimations for each algorithm (PMSI data and registry data correspond to year 2004).

		Algorithm 1					Algorithm 2
Département	Observed cases	PMSI cases	Predicted cases	PE ^1	χ² ^2	RE^3	PMSI cases	Predicted cases	PE^1	χ² ^2	RE^3
Calvados	449	566	487	8	3.0	+8.5	493	480	27.4	2.0	+ 6.8
Doubs	409	495	426	12.8	0.7	+4.2	401	398	34.3	0.3	−2.7
Hérault	919	1,031	872	7.1	2.5	−5.1	900	880	12	1.8	−4.3
Isère	901	1,039	873	9	0.9	−3.1	901	869	8.9	1.2	−3.5
Loire-Atlantique	963	1,138	959	5	0.0	−0.4	1,036	1,019	10.9	3.1	+5.8
Tarn	305	355	306	7.3	0.0	+0.3	306	304	10.1	0.0	−0.5
Total	3,946	4,624	3,923				4,037	3,950

¹PE: prediction error, under the hypothesis that prediction is correct, PE follows a χ² law with 10 degrees of freedom; that is, with a 5%  α-risk, if PE >18.3 then the prediction is not correct for that Département.
²χ² with one degree of freedom, threshold value 3.84.
³RE: relative error; that is, predicted cases-observed cases/observed.