Radiosensitivity Index is Not Fit to be Used for Dose Adjustments: A Pan-Cancer Analysis
To explore the preclinical and latest clinical evidence of the radiation sensitivity signature termed ‘radiosensitivity index’ (RSI), to assess its suitability as an input into dose-adjustment algorithms. The original preclinical test-set data from the publication where RSI was derived were collecte...
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Veröffentlicht in: | Clinical oncology (Royal College of Radiologists (Great Britain)) 2023-09, Vol.35 (9), p.565-570 |
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Zusammenfassung: | To explore the preclinical and latest clinical evidence of the radiation sensitivity signature termed ‘radiosensitivity index’ (RSI), to assess its suitability as an input into dose-adjustment algorithms.
The original preclinical test-set data from the publication where RSI was derived were collected and reanalysed by comparing the observed versus predicted survival fraction at 2 Gy (SF2). In addition, the predictive capability of RSI was also compared to random guessing. Clinical data were collected from a recently published dataset that included RSI values, overall survival outcomes, radiotherapy dose and tumour site for six cancers (glioma, triple-negative breast, endometrial, melanoma, pancreatic and lung cancer). Cox proportional hazards models were used to assess: (i) does adjusting for RSI elucidate a dose response and (ii) does an interaction between RSI and dose exist with good precision.
Preclinically, RSI showed a negative correlation (Spearman's rho = –0.61) between observed and predicted SF2, which remained negative after removing leukaemia cell lines. Furthermore, random guesses showed better correlation to SF2 than RSI, 98% of the time on the full dataset and 80% after removing leukaemia cell lines. The preclinical data show that RSI does not explain the variance in SF2 better than random guessing. Clinically, a dose response was not seen after adjusting for RSI (hazard ratio = 1.00, 95% confidence interval 0.97–1.04; P = 0.876) and no evidence of an interaction between RSI and dose was found (P = 0.844).
These results suggest that RSI does not explain a sufficient amount of the outcome variance to be used within dose-adjustment algorithms.
•Re-analysis of preclinical evidence for RSI was conducted.•Pan-cancer analysis assessing RSI suitability for dosing algorithms was conducted.•Current empirical evidence does not support use of RSI in dosing algorithms. |
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ISSN: | 0936-6555 1433-2981 |
DOI: | 10.1016/j.clon.2023.02.018 |