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Cancer incidence estimation by hospital discharge flow as compared with cancer registries data
被引:0
|作者:
Ferretti, Stefano
[1
]
Guzzinati, Stefano
[2
]
Zambon, Paola
[2
]
Manneschi, Gianfranco
[3
]
Crocetti, Emanuele
[3
]
Falcini, Fabio
[4
]
Giorgetti, Stefania
[4
]
Cirilli, Claudia
[5
]
Pirani, Monica
[5
]
Mangone, Lucia
[6
]
Di Felice, Enza
[6
]
Del Lisi, Vincenzo
[7
]
Sgargi, Paolo
[7
]
Buzzoni, Carlotta
[3
]
Russo, Antonio
[8
]
Paci, Eugenio
[3
]
机构:
[1] Univ Ferrara, Dipartimento Med Sperimentale & Diagnost, Sez Anat Istol & Citol Patol, Registro Tumori Prov Ferrara, I-44100 Ferrara, Italy
[2] IRCCS, Registro Tumori Veneto, Ist Oncol Veneto, Padua, Italy
[3] Ist Studio & Prevenz Oncol, Registro Tumori Toscano, Unita Operat Epidemiol Clin & Descritt, Florence, Italy
[4] Ist Sci Romagnolo Studio & Cura Tumori, Registro Tumori Romagna, Meldola, Forli Cesena, Italy
[5] Ctr Oncol Modenese, Registro Tumori Prov Modena, Modena, Italy
[6] Azienda Sanit Locale Reggio Emilia, Registro Tumori Reggiano, Unita Epidemiol, Dipartimento Sanita Pubbl, Reggio Emilia, Italy
[7] Azienda Osped Univ Parma, Registro Tumori Prov Parma, Unita Operat Oncol, Parma, Italy
[8] Azienda Osped S Carlo Borromeo, Serv Epidemiol & Stat Med, Milan, Italy
来源:
关键词:
cancer registries;
hospital discharge data;
cancer incidence estimate;
BREAST-CANCER;
ALGORITHM;
D O I:
暂无
中图分类号:
R1 [预防医学、卫生学];
学科分类号:
1004 ;
120402 ;
摘要:
Objective: the study evaluates the accuracy of an algorithm based on hospital discharge data (HDD) in order to estimate breast cancer incidence in three italian regions (Emilia-Romagna, Toscana and Veneto) covered by cancer registries (CR). The evolution of computer-based information systems in health organization suggests automatic processing of HDD as a possible alternative to the time-consuming methods of CR. The study Intends to verify whether HDD quickly provides reliable cancer incidence estimates for diagnosis and therapy evaluations. Design and setting: an algorithm based on discharge diagnosis and surgical therapy of hospitalized breast cancer patients was developed in order to provide breast cancer incidence. Results were compared with the corresponding incidence data of cancer registries. The accuracy of the automatic method was also verified by a direct record-linkage between HDD output and registries' files. The overall survival of cases lost to "HDD method" was analyzed. Results: in the period covered by the study (3,125,425 personlyear) CR enrolled 6,079 incident cases, compared to 6, 000 cases recorded through the HDD flow. Incidence rates of the two methods (CR 194.5; HDD 192.0 x 100.000) showed no statistical differences. However matched cases by the two methods were only 5,038. The sensitivity of the HDD algorithm was 82.9% and its predictive positive value (PPV) was 84.0%. False positive cases were 9.9%. On the other hand 12.3% CR incident cases were not identified by the algorithm: these were mainly made tip of older women, not eligible for surgical therapy. Their three-years survival was 62.0% vs 88.8% of the whole incidence group. Conclusion: HDD flow performance was similar to observations reported in the literature. The agreement between HDD and CR incidence rates is a result of a cross effect of both sensitivity and specificity limitations of the HDD algorithm. This can seriously impair the reliability of the latter method with regard to the evaluation of diagnostic and therapeutic strategies in cohort studies (i.e. the most effective approach to health setting in oncology). (Epidemiol Prev 2009; 33 (4-5): 147-53)
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页码:147 / 153
页数:7
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