Epidemiology-based assessment of tumor marker overordering in breast cancer: an algorithm to examine different disease conditions

Use of Routine Health Datasets to Assess the Appropriateness of Diagnostic Tests in the Follow-Up of Breast Cancer Patients: A Population-Based Study on 3930 Patients

Purpose

Clinical practice guidelines (CPGs) recommend against intensive follow-up in asymptomatic women with breast cancer (BC). The present study assessed the adherence to CPGs of diagnostic tests ordering during BC follow-up by exploring routinely collected health data through an algorithm developed to distinguish patients according to their status at follow-up.

Patients and Methods

A retrospective population-based cohort study was performed monitoring the diagnostic tests ordered during 5 years of follow-up in all BC cases incident in 2013 in the Veneto Region, Italy. Data were extracted from the Veneto Tumour Registry, the Hospital Discharge Records and the Outpatients’ Records of Diagnostic and Therapeutic Procedures. The algorithm was developed using information on infusion of anticancer agents, imaging exams ordered, and death.

Results

The algorithm classified patients by status at follow-up in four groups: (i) probably no-evidence-of-disease (NED), (ii) suspicious signs of relapse not confirmed, (iii) increased risk of relapse and (iv) advanced disease at presentation or progressive disease. A total of 3930 consecutive incident cases were followed-up for 5 years, corresponding to 17,184 person-years, 15,345 of which pertaining to NED cases. In NED cases, 32,900 tumour markers and 15,858 imaging exams were ordered. Liver ultrasonography and chest radiography were most frequently ordered.

Conclusion

In contrast with recommendations of CPGs, a substantial overordering of tumour markers and imaging exams occurred in NED BC patients. The developed algorithm can be repeatedly applied to routine health datasets for regular monitoring of the adherence to CPGs and of the impact of interventions to improve appropriateness.

Appropriateness of tumor marker request: a case of study

Appropriateness is crucial to provide efficient and high-quality health services at affordable costs. Laboratory medicine is a sector of special interest for the investigation of inappropriateness, due to the high rate of technological innovation and its pivotal role in many diseases and clinical settings. Some subjective aspects related to either the patient or physician seem to have a major role on inappropriateness rates. Given the psychological impact of cancer on both patients and physicians, tumor markers represent a case of study for appropriateness. The assessment of inappropriateness of laboratory tests has been focused mainly on ordering patterns. Appropriateness can barely be appraised by matching the requested test with the clinical problem because clinical information on the test requisition form is usually inadequate. Monitoring inappropriateness through individual clinical information may be feasible in inpatient (clinical data are available), while an indirect approach should be used for outpatients. To estimate inappropriateness in outpatients our group developed innovative models based on comparison between the actually ordered and expected requests of tumor marker, calculated according to recommendations of clinical practice guidelines (CPGs) applied to figures of cancer prevalence. The implementation of the model at national scale in Italy led to recognize a very high rate of overordering of tumor markers. The model was further focused by a dedicated algorithm to be adapted to different clinical conditions or organizational settings by applying performance indicators to cohort-wide structured information in electronic health records (EHRs). With this novel approach, we showed that inappropriateness is multifaceted even within the specific category of tumour markers. The model was effective in identifying both over- and underordering. Implementation of evidence based information and monitoring their impact on the clinical practice are parts of the same, multistage, process aimed at the progressive improvement of health care.