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Accuracy of administrative databases in detecting primary breast cancer diagnoses: a systematic review
  1. Iosief Abraha1,2,
  2. Alessandro Montedori1,
  3. Diego Serraino3,
  4. Massimiliano Orso1,2,
  5. Gianni Giovannini1,
  6. Valeria Scotti4,
  7. Annalisa Granata5,
  8. Francesco Cozzolino1,
  9. Mario Fusco5,
  10. Ettore Bidoli3
  1. 1 Health Planning Service, Regional Health Authority of Umbria, Perugia, Italy
  2. 2 Innovation and Development, Agenzia Nazionale per i Servizi Sanitari Regionali (Age.Na.S.), Rome, Italy
  3. 3 Cancer Epidemiology Unit, IRCCS Centro di Riferimento Oncologico Aviano, Aviano, Italy
  4. 4 Center for Scientific Documentation, IRCCS Policlinico S. Matteo Foundation, Pavia, Italy
  5. 5 Registro Tumori Regione Campania, ASL Napoli 3 Sud, Brusciano, Italy
  1. Correspondence to Dr Alessandro Montedori; amontedori{at}regione.umbria.it

Abstract

Objective To define the accuracy of administrative datasets to identify primary diagnoses of breast cancer based on the International Classification of Diseases (ICD) 9th or 10th revision codes.

Design Systematic review.

Data sources: MEDLINE, EMBASE, Web of Science and the Cochrane Library (April 2017).

Eligibility criteria The inclusion criteria were: (a) the presence of a reference standard; (b) the presence of at least one accuracy test measure (eg, sensitivity) and (c) the use of an administrative database.

Data extraction Eligible studies were selected and data extracted independently by two reviewers; quality was assessed using the Standards for Reporting of Diagnostic accuracy criteria.

Data analysis Extracted data were synthesised using a narrative approach.

Results From 2929 records screened 21 studies were included (data collection period between 1977 and 2011). Eighteen studies evaluated ICD-9 codes (11 of which assessed both invasive breast cancer (code 174.x) and carcinoma in situ (ICD-9 233.0)); three studies evaluated invasive breast cancer-related ICD-10 codes. All studies except one considered incident cases.

The initial algorithm results were: sensitivity ≥80% in 11 of 17 studies (range 57%–99%); positive predictive value was ≥83% in 14 of 19 studies (range 15%–98%) and specificity ≥98% in 8 studies. The combination of the breast cancer diagnosis with surgical procedures, chemoradiation or radiation therapy, outpatient data or physician claim may enhance the accuracy of the algorithms in some but not all circumstances. Accuracy for breast cancer based on outpatient or physician’s data only or breast cancer diagnosis in secondary position diagnosis resulted low.

Conclusion Based on the retrieved evidence, administrative databases can be employed to identify primary breast cancer. The best algorithm suggested is ICD-9 or ICD-10 codes located in primary position.

Trial registration number CRD42015026881.

  • breast cancer
  • administrative database
  • validity
  • accuracy
  • sensitivity and specificity
  • systematic review

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Footnotes

  • Contributors IA, AM, GG, DG, MF conceived and designed the study; EB, VS, AG, FC, MO, IA and AM were involved in the data acquisition; IA, AM, DS, MF and GG analysed and interpreted the data and IA, EB, MO, GG, DS, VS, AG, FC, MF and AM contributed in the drafting and revising the study and have approved submission of the final version of the article. AM is the guarantor of the review.

  • Funding This systematic review protocol was developed within the D.I.V.O. project (Realizzazione di un Database Interregionale Validato per l’Oncologia quale strumento di valutazione di impatto e di appropriatezza delle attività di prevenzione primaria e secondaria in ambito oncologico) supported by funding from the National Centre for Disease Prevention and Control (CCM 2014), Ministry of Health, Italy.

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement The authors will give full access to our database that gathered data of individual studies included in this review. The request must be done by sending an email to amontedori@regione.umbria.it.

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