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

Abstract

Objective. Use of cancer cases from registries and PMSI claims database to estimate Département-specific incidence of four major cancers. Methods. Case extraction used principal diagnosis then surgery codes. PMSI cases/registry cases ratios for 2004 were modelled then Département-specific incidence for 2007 estimated using these ratios and 2007 PMSI cases. Results. For 2007, only colon-rectum and breast cancer estimations were satisfactorily validated for infranational incidence not ovary and kidney cancers. For breast, the estimated national incidence was 50,578 cases and the incidence rate 98.6 cases per 100,000 person per year. For colon-rectum, incidence was 21,172 in men versus 18,327 in women and the incidence rate 38 per 100,000 versus 24.8. For ovary, the estimated incidence was 4,637 and the rate 8.6 per 100,000. For kidney, incidence was 6,775 in men versus 3,273 in women and the rate 13.3 per 100.000 versus 5.2. Conclusion. Incidence estimation using PMSI patient identifiers proved encouraging though still dependent on the assumption of uniform cancer treatments and coding.

Evaluation of algorithms to identify incident cancer cases by using French health administrative databases

“…Many studies have shown the importance of health administrative databases in estimating cancer incidence . Most of these were based on inpatient data to validate cancer cases .…”

“…Many studies have developed methods to identify incident cancers by using health administrative databases . However, given that no ‘date of diagnosis’ variable exists in these databases, the main difficulty remains in the ability to distinguish between prevalent and incident cases, a key issue for etiological cancer studies.…”

“…Many studies have developed methods to identify incident cancers by using health administrative databases. [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] However, given that no 'date of diagnosis' variable exists in these databases, the main difficulty remains in the ability to distinguish between prevalent and incident cases, a key issue for etiological cancer studies. Couris et al, in a systematic review of the use of claim databases to identify incident cancer cases, underlined the amount of false-positive cancers because of the prevalent cases included.…”

A data mining approach for grouping and analyzing trajectories of care using claim data: the example of breast cancer

“…However, they strongly depend on the algorithm used to select patients and build the care trajectory. Several studies have assessed the use of administrative databases to detect cancer cases [12,36,37]. Our method selects patients with surgical breast cancer on a combination of diagnosis and procedure codes which can reduce the false positive rate [38].…”

Quality indicators for colorectal cancer surgery and care according to patient-, tumor-, and hospital-related factors

“…Incidences from this regional administrative hospital and regional medical information system (further abbreviated as RMIS) have been validated against national incidences from the national register (FRANCIM) [18]. …”