Title |
Predicting cumulative incidence of adverse events in older patients with cancer undergoing first-line palliative chemotherapy: Korean Cancer Study Group (KCSG) multicentre prospective study
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Published in |
British Journal of Cancer, March 2018
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DOI | 10.1038/s41416-018-0037-6 |
Pubmed ID | |
Authors |
Jin Won Kim, Yun-Gyoo Lee, In Gyu Hwang, Hong Suk Song, Su Jin Koh, Yoon Ho Ko, Seong Hoon Shin, In Sook Woo, Soojung Hong, Tae-Yong Kim, Sun Young Kim, Byung-Ho Nam, Hyun Jung Kim, Hyo Jung Kim, Myung Ah Lee, Jung Hye Kwon, Yong Sang Hong, Sung Hwa Bae, Dong-Hoe Koo, Kwang-Il Kim, Jee Hyun Kim |
Abstract |
Older patients have increased risk of toxicity from chemotherapy. Current prediction tools do not provide information on cumulative risk. Patients aged ≥ 70 years with solid cancer were prospectively enrolled. A prediction model was developed for adverse events (AEs) ≥ Grade 3 (G3), based on geriatric assessment (GA), laboratory, and clinical variables. 301 patients were enrolled (median age, 75 years). Median number of chemotherapy cycles was 4. During first-line chemotherapy, 53.8% of patients experienced AEs ≥ G3. Serum protein < 6.7 g/dL, initial full-dose chemotherapy, psychological stress or acute disease in the past 3 months, water consumption < 3 cups/day, unable to obey a simple command, and self-perception of poor health were significantly related with AEs ≥ G3. A predicting model with these six variables ranging 0-8 points was selected with the highest discriminatory ability (c-statistic= 0.646), which could classify patients into four risk groups. Predicted cumulative incidence of AEs ≥ G3 was discriminated according to risk groups. This prediction tool could identify the risk of AEs ≥ G3 after chemotherapy and provide information on the cumulative incidence of AEs in each cycle. WHO ICTRP number, KCT0001071. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Australia | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 75% |
Scientists | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 65 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 12 | 18% |
Student > Bachelor | 9 | 14% |
Other | 6 | 9% |
Student > Postgraduate | 4 | 6% |
Student > Ph. D. Student | 4 | 6% |
Other | 7 | 11% |
Unknown | 23 | 35% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 12 | 18% |
Nursing and Health Professions | 10 | 15% |
Biochemistry, Genetics and Molecular Biology | 6 | 9% |
Pharmacology, Toxicology and Pharmaceutical Science | 6 | 9% |
Psychology | 4 | 6% |
Other | 4 | 6% |
Unknown | 23 | 35% |