International journal of radiation oncology, biology, physics · 2017
Development and Internal Validation of a Clinical Risk Score to Predict Pain Response After Palliative Radiation Therapy in Patients With Bone Metastases.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
van der Velden Joanne M, Peters Max, Verlaan Jorrit-Jan, Versteeg Anne L, Zhang Liying, Tsao May, Danjoux Cyril, Barnes Elizabeth, van Vulpen Marco, Chow Edward, Verkooijen Helena M
Аннотация
PURPOSE: To investigate the relationship between patient and tumor characteristics and pain response in patients with metastatic bone disease, and construct and internally validate a clinical prediction model for pain response to guide individualized treatment decision making.
MATERIAL AND METHODS: A total of 965 patients with painful bone metastases undergoing palliative radiation therapy at a tertiary referral center between 1999 and 2007 were identified. Pain scores were measured at 1, 2, and 3 months after radiation therapy. Pain response was defined as at least a 2-point decrease on a pain score scale of 0-10, without increase in analgesics, or an analgesic decrease of at least 25% without an increase in pain score. Thirteen candidate predictors were identified from the literature and expert experience. After multiple imputation, final predictors were selected using stepwise regression and collapsed into a prediction model. Model performance was evaluated by calibration and discrimination and corrected for optimism.
RESULTS: Overall 462 patients (47.9%) showed a response. Primary tumor site, performance status, and baseline pain score were predictive for pain response, with a corrected c-statistic of 0.63. The predicted response rates after radiation therapy increased from 37.5% for patients with the highest risk score to 79.8% for patients with the lowest risk score and were in good agreement with the observed response rates.
CONCLUSIONS: A prediction score for pain response after palliative radiation therapy was developed. The model performance was moderate, showing that prediction of pain response is difficult. New biomarkers and predictors may lead to improved identification of the large group of patients who are unlikely to respond and who may benefit from other or innovative treatment options.
MATERIAL AND METHODS: A total of 965 patients with painful bone metastases undergoing palliative radiation therapy at a tertiary referral center between 1999 and 2007 were identified. Pain scores were measured at 1, 2, and 3 months after radiation therapy. Pain response was defined as at least a 2-point decrease on a pain score scale of 0-10, without increase in analgesics, or an analgesic decrease of at least 25% without an increase in pain score. Thirteen candidate predictors were identified from the literature and expert experience. After multiple imputation, final predictors were selected using stepwise regression and collapsed into a prediction model. Model performance was evaluated by calibration and discrimination and corrected for optimism.
RESULTS: Overall 462 patients (47.9%) showed a response. Primary tumor site, performance status, and baseline pain score were predictive for pain response, with a corrected c-statistic of 0.63. The predicted response rates after radiation therapy increased from 37.5% for patients with the highest risk score to 79.8% for patients with the lowest risk score and were in good agreement with the observed response rates.
CONCLUSIONS: A prediction score for pain response after palliative radiation therapy was developed. The model performance was moderate, showing that prediction of pain response is difficult. New biomarkers and predictors may lead to improved identification of the large group of patients who are unlikely to respond and who may benefit from other or innovative treatment options.