Joo Ho Lee1,2, Changhoon Song1, Sung-Bum Kang3, Hye Seung Lee4, Keun-Wook Lee5, Jae-Sung Kim6. 1. Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. 2. Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea. 3. Department of Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. 4. Department of Pathology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. 5. Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. 6. Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea jskim@snubh.org.
Abstract
BACKGROUND: This study evaluated the efficacy of haematological markers for predicting the pathological complete regression (pCR) during and after neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced rectal cancer (LARC). PATIENTS AND METHODS: A total of 297 patients with LARC underwent neoadjuvant CRT followed by surgical resection. Complete blood counts (CBCs) were performed before CRT, 3 weeks after the start of CRT (intra-therapy), and 4 weeks after CRT. Platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) were calculated using the serial CBC test. The ratio of change in PLR (cPLR) and NLR (cNLR) was calculated as the increase from the pre-therapy value to intra-therapy or post-therapy value divided by the pre-therapy value. Chi-square and t-test for univariate analysis and multivariate logistic regression were performed to identify significant predictors for pCR. Receiver operating characteristic (ROC) analysis was used to compare predictive values. RESULTS: The overall rate of pCR was 15.9%. Pre-therapy high haemoglobin and low NLR; intra-therapy high PLR, high NLR, high cPLR, and high cNLR; and post-therapy low white blood cell count (WBC), high haemoglobin, and high cPLR were significantly associated with pCR. In multivariate logistic regression, pre-therapy high haemoglobin [odds ratio (OR)=1.500, p=0.016], high intra-therapy PLR (OR=1.006, p=0.011), high intra-therapy cPLR (OR=4.948, p<0.001), and low post-therapy WBC (OR=0.639, p=0.003) were significant predictors for pCR. ROC analysis showed that high intra-therapy cPLR was the most accurate predictor of pCR (area under the curve=0.741). CONCLUSION: Changes of PLR during neoadjuvant CRT for LARC are significant predictors of pCR. Copyright
BACKGROUND: This study evaluated the efficacy of haematological markers for predicting the pathological complete regression (pCR) during and after neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced rectal cancer (LARC). PATIENTS AND METHODS: A total of 297 patients with LARC underwent neoadjuvant CRT followed by surgical resection. Complete blood counts (CBCs) were performed before CRT, 3 weeks after the start of CRT (intra-therapy), and 4 weeks after CRT. Platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) were calculated using the serial CBC test. The ratio of change in PLR (cPLR) and NLR (cNLR) was calculated as the increase from the pre-therapy value to intra-therapy or post-therapy value divided by the pre-therapy value. Chi-square and t-test for univariate analysis and multivariate logistic regression were performed to identify significant predictors for pCR. Receiver operating characteristic (ROC) analysis was used to compare predictive values. RESULTS: The overall rate of pCR was 15.9%. Pre-therapy high haemoglobin and low NLR; intra-therapy high PLR, high NLR, high cPLR, and high cNLR; and post-therapy low white blood cell count (WBC), high haemoglobin, and high cPLR were significantly associated with pCR. In multivariate logistic regression, pre-therapy high haemoglobin [odds ratio (OR)=1.500, p=0.016], high intra-therapy PLR (OR=1.006, p=0.011), high intra-therapy cPLR (OR=4.948, p<0.001), and low post-therapy WBC (OR=0.639, p=0.003) were significant predictors for pCR. ROC analysis showed that high intra-therapy cPLR was the most accurate predictor of pCR (area under the curve=0.741). CONCLUSION: Changes of PLR during neoadjuvant CRT for LARC are significant predictors of pCR. Copyright