Novel longitudinal Multiple Overall Toxicity (MOTox) score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma
BMJ Open, vol. 11, pp. e053456
Abstract
OBJECTIVES: This study aims at exploring and quantifying multiple types of adverse events (AEs) experienced by patients during cancer treatment. A novel longitudinal score to evaluate the Multiple Overall Toxicity (MOTox) burden is proposed. The MOTox approach investigates the personalised evolution of high overall toxicity (high-MOTox) during the treatment. DESIGN: Retrospective analysis of the MRC-BO06/EORTC-80931 randomised controlled trial for osteosarcoma. SETTING: International multicentre population-based study. PARTICIPANTS: A total of 377 patients with resectable high-grade osteosarcoma, who completed treatment within 180 days after randomisation without abnormal dosages (+25% higher than planned). INTERVENTIONS: Patients were randomised to six cycles of conventional versus dose-intense regimens of doxorubicin and cisplatin. Non-haematological toxicity data were collected prospectively and graded according to the Common Terminology Criteria for Adverse Events (CTCAE). MAIN OUTCOME MEASURES: The MOTox score described the overall toxicity burden in terms of multiple toxic AEs, maximum-severity episode and cycle time-dimension. Evolution of high-MOTox was assessed through multivariable models, that investigated the impact of personalised characteristics (eg, achieved chemotherapy dose, previous AEs or biochemical factors) cycle-by-cycle. RESULTS: MOTox conditions during previous cycles were prognostic risk factors for a new occurrence (ORs range from 1.522 to 4.439), showing that patient's history of toxicities played an important role in the evolution of overall toxicity burden during therapy. Conventional regimen may be preferred to dose-intense in terms of AEs at cycles 2-3 (p<0.05). CONCLUSIONS: The novel longitudinal method developed can be applied to any cancer studies with CTCAE-graded toxicity data. After validation in other studies, the MOTox approach may lead to improvements in healthcare assessment and treatment planning. TRIAL REGISTRATION NUMBER: ISRCTN86294690; Post-results.
Authors 10
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Leiden University · University of Milano-Bicocca · Politecnico di Milano
Affiliation as printed
CHRP - National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy marta.spreafico@polimi.it
Mathematical Institute, Leiden University, Leiden, Netherlands
CHRP – National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Human Technopole · University of Milano-Bicocca · Politecnico di Milano
Affiliation as printed
CHDS - Centre for Health Data Science, Human Technopole, Milan, Italy
CHRP - National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
CHDS – Centre for Health Data Science, Human Technopole, Milan, Italy
CHRP – National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
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Affiliation as printed
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Affiliation as printed
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Affiliation as printed
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Affiliation as printed
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Affiliation as printed
MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Affiliation as printed
Department of Solid Tumors, Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
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Leiden University Medical Center
Affiliation as printed
Department of Medical Oncology, Leiden University Medical Center, Leiden, Netherlands
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Leiden University · Leiden University Medical Center · Princess Máxima Center
Affiliation as printed
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
Mathematical Institute, Leiden University, Leiden, Netherlands
Trial and Data Center, Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
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