Factors associated with the initiation of chemotherapy within 90 days of death in metastatic colorectal cancer patients: a population-based study.

INTRODUCTION: Initiation of chemotherapy in patients with cancer near end-of-life (EOL) has become more frequent due to an increasing number of treatment options. We aimed to analyze the proportion of metastatic colorectal cancer patients (mCRC) in Alberta, Canada, who were started on a new chemotherapy regimen within 90 days of death. METHODS: This was a retrospective, population-based study using data from the cancer measurement outcomes and evaluation (C-MORE) database. All patients who received chemotherapy for mCRC in a large Canadian province from January 1, 2011, to December 31, 2016, were included in the current analysis. We identified the proportion of patients who initiated chemotherapy near EOL. Further, we analyzed the associations of baseline factors with initiation of chemotherapy near EOL. RESULTS: We identified 511 patients with mCRC who received chemotherapy. Of these, 132 (25.8%) initiated chemotherapy near EOL. Charlson's comorbidity index (CCI) score (score 1: OR, 0.524; 95% CI, 0.279-0.985; P = 0.045; CCI score > 1: OR, 0.366; 95% CI, 0.180-0.746; P = 0.006) and Eastern cooperative oncology group performance status (ECOG PS) (ECOG PS 2: OR, 4.457; 95% CI 2.518-7.890; P < 0.0001; ECOG PS > 2: OR 7.725; 95% CI 3.465-17.222; P < 0.0001) were predictive of initiation of chemotherapy near EOL. The most frequent chemotherapy regimens initiated were FOLFIRI (17%), capecitabine (15%), and panitumumab (15%), respectively. CONCLUSIONS: Chemotherapy is frequently initiated near EOL in patients with mCRC. Routine clinical assessments including ECOG PS and comorbid medical conditions can help select patients with mCRC who are unlikely to benefit from palliative chemotherapy and prevent the adverse events and healthcare costs associated with such interventions near EOL.

Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data.

BACKGROUND: Recurrence is not explicitly documented in cancer registry data that are widely used for research. Patterns of events after initial treatment such as oncology visits, re-operation, and receipt of subsequent chemotherapy or radiation may indicate recurrence. This study aimed to develop and validate algorithms for identifying breast cancer recurrence using routinely collected administrative data. METHODS: The study cohort included all young (≤ 40 years) breast cancer patients (2007-2010), and all patients receiving neoadjuvant chemotherapy (2012-2014) in Alberta, Canada. Health events (including mastectomy, chemotherapy, radiation, biopsy and specialist visits) were obtained from provincial administrative data. The algorithms were developed using classification and regression tree (CART) models and validated against primary chart review. RESULTS: Among 598 patients, 121 (20.2%) had recurrence after a median follow-up of 4 years. The high sensitivity algorithm achieved 94.2% (95% CI: 90.1-98.4%) sensitivity, 93.7% (91.5-95.9%) specificity, 79.2% (72.5-85.8%) positive predictive value (PPV), and 98.5% (97.3-99.6%) negative predictive value (NPV). The high PPV algorithm had 75.2% (67.5-82.9%) sensitivity, 98.3% (97.2-99.5%) specificity, 91.9% (86.6-97.3%) PPV, and 94% (91.9-96.1%) NPV. Combining high PPV and high sensitivity algorithms with additional (7.5%) chart review to resolve discordant cases resulted in 94.2% (90.1-98.4%) sensitivity, 98.3% (97.2-99.5%) specificity, 93.4% (89.1-97.8%) PPV, and 98.5% (97.4-99.6%) NPV. CONCLUSION: The proposed algorithms based on routinely collected administrative data achieved favorably high validity for identifying breast cancer recurrences in a universal healthcare system in Canada.