[Development and validation of an algorithm to identify cancer recurrences from hospital data bases]
S Manzanares-Laya1, A Burón2, C Murta-Nascimento2
1Servei d'Epidemiologia i Avaluació, Hospital del Mar-Parc de Salut Mar, Barcelona, España; Unitat Docent de Medicina Preventiva i Salut Pública, H. MAR-UPF-ASPB, Barcelona, España.
Objectives:
Hospital cancer registries and hospital databases are valuable and efficient sources of information for research into cancer recurrences. The aim of this study was to develop and validate algorithms for the detection of breast cancer recurrence.
Methods:
A retrospective observational study was conducted on breast cancer cases from the cancer registry of a third level university hospital diagnosed between 2003 and 2009. Different probable cancer recurrence algorithms were obtained by linking the hospital databases and the construction of several operational definitions, with their corresponding sensitivity, specificity, positive predictive value and negative predictive value.
Results:
A total of 1,523 patients were diagnosed of breast cancer between 2003 and 2009. A request for bone gammagraphy after 6 months from the first oncological treatment showed the highest sensitivity (53.8%) and negative predictive value (93.8%), and a pathology test after 6 months after the diagnosis showed the highest specificity (93.8%) and negative predictive value (92.6%). The combination of different definitions increased the specificity and the positive predictive value, but decreased the sensitivity.
Conclusions:
Several diagnostic algorithms were obtained, and the different definitions could be useful depending on the interest and resources of the researcher. A higher positive predictive value could be interesting for a quick estimation of the number of cases, and a higher negative predictive value for a more exact estimation if more resources are available. It is a versatile and adaptable tool for other types of tumors, as well as for the needs of the researcher.
