French claims data as a source of information to describe cancer incidence: predictive values of two identification methods of incident prostate cancers.
Claims data from the "Programme de Médicalisation du Système d'Information" (PMSI) have been commonly used for several years to complement cancer registries and describe cancer incidence in France. It is less clear whether or not it is possible to use these data as an independent source of information to assess cancer incidence, in the absence of a regional cancer registry. Following a similar study on breast cancer, we present a study which aimed to evaluate two methods of identifying incident prostate cancer using claims data. These methods were developed using claims data from the Hospices Civils de Lyon (HCL) and their validity was tested against medical records. The first method (M1) identified incident patients as those who had at least one stay with a principal diagnosis of prostate cancer. The second method (M2) had a prostate cancer treatment code in addition to the criteria for the first method. Both methods of identification had similar results, indicating a low rate of false negatives (negative predictive values: M1 = 100 [CI95: 93.8-100], M2 = 98.6 [CI95: 90.1-99.6]) and a high rate of false positives (positive predictive values: M1 = 33.3 [CI95: 23.2-42.1], M2 = 33.7 [CI95: 24.2-43.2]). The sample size did not allow us to produce consistent estimates of sensitivity and specificity. Our results showed that an estimation of the number of incident cases of prostate cancer using both methods of identification would be biased because of the high rate of false positives. Statistical methods that correct identification errors should be used.
Couris
Chantal Marie
CM
Département d'Information médicale des Hospices Civils de Lyon, 162, avenue, Lacassagne, 69424 Lyon cedex 03. chantal.couris@chu-lyon.fr
Seigneurin
Arnaud
A
Bouzbid
Sabiha
S
Rabilloud
Muriel
M
Perrin
Paul
P
Martin
Xavier
X
Colin
Cyrille
C
Schott
Anne-Marie
AM
D005602:France / Q000453:epidemiology; D006801:Humans; D007345:Insurance Claim Review; D008297:Male; D008499:Medical Records; D011237:Predictive Value of Tests; D011471:Prostatic Neoplasms / Q000453:epidemiology*; D012042:Registries