| Abstrakt: |
Background: On average 20% of patients require a systemic anti-cancer treatment (SACT) delay.1 The risk of toxicity-related dose delays, with SACT, should be included as part of pre-treatment education and be considered by clinicians upon prescribing chemotherapy. An objective measure of individual risk could influence clinical decisions, such as the escalation of standard supportive care and stratification of some patients, to receive proactive toxicity monitoring. The understanding of this risk may also support the advanced preparation of treatments for those that have a lower risk of delay. Data available within hospital systems can support the understanding of risk through the development of a risk score. In this study, we developed and validated a score to assess the risk of a SACT dose delay of 7 days (delay-7 score). Objectives: To develop and internally validate a risk score to predict the occurrence of a 7-day dose delay for patients receiving cycle 1 treatments for breast and colorectal cancers and diffuse large b-cell lymphomas. To assess the discrimination and calibration of the model. Methods: Four hospitals were included in our study, recruited through BOPA. Data were collected for patients aged 18 or over, identified through the chemotherapy prescribing systems at each hospital for the period of 1 January 2013 to 1 January 2018. The first chemotherapy treatment date was used as the index date for entry to the cohort during the study period. The study data was restricted to the following three tumour groups: breast, colorectal and diffuse large B-Cell lymphoma. Data included hospital treatment, age at the start of SACT, gender, ethnicity, body mass index, cancer diagnosis, chemotherapy regimen, colony-stimulating factor use, first cycle dose modifications and baseline blood values. Baseline blood values included neutrophils, platelets, haemoglobin, creatinine and bilirubin. A risk prediction model was developed using multivariable logistic regression and all analysis methods complied with the Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD).2 Shrinkage was used to adjust for over-optimism of predictor effects. For internal validation (of the full models in the development data) we computed the ability of the models to discriminate between those with and without poor outcomes (c-statistic), and the agreement between predicted and observed risk (calibration slope). Results: A total of 4604 patients were included in our study of which 628 (13.6%) incurred a 7-day delay to the second cycle of chemotherapy. Delay-7 showed good discrimination and calibration, with a c-statistic of 0.68 [95% confidence interval (CI) 0.66–0.7], following internal validation and calibration-in-the-large of −0.006. Conclusions: Delay-7 predicts a patient’s individualised risk of a treatment-related delay at cycle two of treatment. The score can be used to stratify interventions to reduce the occurrence of treatment-related toxicity. However, to be used in the clinical setting a prospective study should be conducted to ensure the reliability of the score. Nonetheless, we have identified that the score can be useful to support advance preparation in pharmacy aseptic units and a small validation in this setting is planned. [ABSTRACT FROM AUTHOR] |
