Absolute lymphocyte count is an independent predictor of survival in patients with metastatic renal cell carcinoma treated with nivolumab

Ueda, Kousuke; Suekane, Shigetaka; Kurose, Hirofumi; Ogasawara, Naoyuki; Hiroshige, Tasuku; Chikui, Katsuaki; Uemura, Keiichiro; Nakiri, Makoto; Nishihara, Kiyoaki; Matsuo, Mitsuyoshi; Igawa, Tsukasa

doi:10.1093/jjco/hyab157

Cited by 12 publications

(10 citation statements)

References 23 publications

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“…Although white blood cells only account for 0.2% of whole blood, they play an important role in protecting human health [1]. White blood cells are generally divided into neutrophils, eosinophils, basophils, monocytes, and lymphocytes [2], and changes in these cell counts can be used as the basis for diagnosing certain diseases or evaluating the therapeutic efect of certain diseases [3][4][5][6][7][8][9]. Terefore, the accuracy and efciency of white blood cell detection and classifcation are very important for the auxiliary diagnosis of diseases [10].…”

Section: Introductionmentioning

confidence: 99%

A Method for Expanding the Training Set of White Blood Cell Images

Yang

Zang

et al. 2022

Journal of Healthcare Engineering

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In medicine, the count of different types of white blood cells can be used as the basis for diagnosing certain diseases or evaluating the treatment effects of diseases. The recognition and counting of white blood cells have important clinical significance. But the effect of recognition based on machine learning is affected by the size of the training set. At present, researchers mainly rely on image rotation and cropping to expand the dataset. These methods either add features to the white blood cell image or require manual intervention and are inefficient. In this paper, a method for expanding the training set of white blood cell images is proposed. After rotating the image at any angle, Canny is used to extract the edge of the black area caused by the rotation and then fill the black area to achieve the purpose of expanding the training set. The experimental results show that after using the method proposed in this paper to expand the training set to train the three models of ResNet, MobileNet, and ShuffleNet, and comparing the original dataset and the method trained by the simple rotated image expanded dataset, the recognition accuracy of the three models is obviously improved without manual intervention.

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Section: Introductionmentioning

confidence: 99%

A Method for Expanding the Training Set of White Blood Cell Images

Yang

Zang

et al. 2022

Journal of Healthcare Engineering

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“…In our patients, the rapid increase in absolute lymphocyte counts mainly contributed to the increase in post-PNI values. Elevation of absolute lymphocyte counts after the induction of ICIs has been reported in several cancers, including melanoma, non-small cell lung cancer, and renal cell carcinoma (25)(26)(27)(28)(29). These studies demonstrated that higher absolute lymphocyte counts after the start of ICI (3-6 weeks) led to longer survival.…”

Section: Discussionmentioning

confidence: 81%

Prognostic nutritional index of early post‑pembrolizumab therapy predicts long‑term survival in patients with advanced urothelial carcinoma

et al. 2022

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Pembrolizumab has been widely used to treat advanced urothelial carcinoma that has progressed after first-line platinum-based chemotherapy. Because its clinical benefits are limited, biomarkers that can predict a good response to pembrolizumab are required. The prognostic nutritional index (PNI), calculated using the serum albumin level and peripheral lymphocyte count, has been evaluated as a predictive biomarker in cancer immunotherapy. The present study investigated the application of PNI as a predictive biomarker for pembrolizumab response in patients with advanced urothelial cancer. A retrospective study was conducted on 34 patients treated with pembrolizumab at Shiga University of Medical Science Hospital between January 2018 and July 2022. The posttreatment PNI (post-PNI) was calculated within 2 months of starting pembrolizumab. The present study investigated the association between post-PNI and objective response, overall survival (OS) and progression-free survival (PFS). The patient cohort was stratified into two categories, high and low post-PNI groups, with a cutoff value of post-PNI at 40. The higher post-PNI group demonstrated a better disease control rate than the lower post-PNI group (complete response + partial response + stable disease, 75 vs. 21%, P= 0.004). Regarding median OS, the higher post-PNI group exhibited a significantly longer survival time than the lower post-PNI group (23.1 vs. 2.9 months, P<0.001). Similarly, the higher post-PNI group exhibited a significantly longer PFS than the lower post-PNI group (10.2 vs.1.9 months, P<0.001). Multivariate analysis showed that a higher post-PNI value was an independent predictor for OS (hazard ratio, 0.04; 95% confidence interval, 0.01-0.14; P<0.001) and PFS (hazard ratio, 0.12; 95% confidence interval, 0.04-0.35; P<0.001). The present study indicated that the post-PNI was a predictor of favorable clinical outcomes in patients treated with pembrolizumab for advanced urothelial carcinoma.

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“…Karantanous et al reported that lung cancer patients with an ALC ≥1,700/µl have a better OS than for those with <900/µl ( 16 ). Ueda et al demonstrated that the optimal cut-off value of ALC for predicting PFS was 1,300/µl and that an ALC ≥1,300/µl is an independent prognostic factor in metastatic renal cell carcinoma patients ( 28 ). In gastric cancer, Ogata et al ( 18 ) set the cut-off value for NLR in unresectable or recurrent gastric cancer at 5, whereas Yamada et al ( 17 ) set it at 2.5; therefore, the cut-off value differs among studies.…”

Section: Discussionmentioning

confidence: 99%

“…To the best of our knowledge, this is the first report to predict the outcome and side effects of nivolumab therapy for recurrent esophageal cancer using only blood biochemical examination, such as ACL, NLR, PLR, MLR, and CAR values, or a simple score, PS. As nivolumab therapy for recurrent esophageal cancer is expected to become increasingly widespread, prediction of the prognosis and side effects is essential ( 15 – 21 , 28 ). The more accurate and predictable a measure is using a simple method, the more frequently it will be used; therefore, ALC and CAR as predictors of the outcome and side effects of nivolumab therapy for recurrent esophageal cancer may be versatile.…”

Section: Discussionmentioning

confidence: 99%

Absolute lymphocyte count and C‑reactive protein‑albumin ratio can predict prognosis and adverse events in patients with recurrent esophageal cancer treated with nivolumab therapy

et al. 2022

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Predicting the prognosis and adverse events (AEs) of nivolumab therapy for recurrent esophageal cancer is very important. The present study investigated whether a simple blood biochemical examination could be used to predict prognosis and AEs following nivolumab treatment for relapse of esophageal cancer. A total of 41 patients who received nivolumab treatment for recurrent esophageal cancer after esophagectomy were analyzed. The absolute lymphocyte count (ALC), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR) and C-reactive protein-albumin ratio (CAR) were assessed at the time of nivolumab induction as indices that can be calculated by blood biochemical examinations alone. Median values were 1,015 for ALC, 3.401 for NLR, 242.6 for PLR, 0.458 for MLR and 0.119 for CAR, and patients were divided into two groups according to values. A high ALC, low NLR, low PLR, low MLR and low CAR were associated with a better response to nivolumab. In addition, patients with the aforementioned indices, with the exception of low PLR, or better response were more likely to develop AEs in univariate analysis. In multivariate analysis, a high ALC [odds ratio (OR): 4.857, P=0.043] and low CAR (OR: 9.099, P=0.004) were identified as independent risk factors for AEs. Survival analysis revealed that overall survival and progression-free survival (PFS) rates after nivolumab treatment differed significantly between the high and low groups of ALC, NLR, PLR, MLR and CAR. The multivariate analysis identified a low ALC [hazard ratio (HR): 3.710, P=0.003] and high CAR (HR: 2.953, P=0.007) as independent poor prognostic factors of PFS. In conclusion, ALC and CAR have potential as biomarkers for outcomes of recurrent esophageal cancer following nivolumab treatment.

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Absolute lymphocyte count is an independent predictor of survival in patients with metastatic renal cell carcinoma treated with nivolumab

Cited by 12 publications

References 23 publications

A Method for Expanding the Training Set of White Blood Cell Images

A Method for Expanding the Training Set of White Blood Cell Images

Prognostic nutritional index of early post‑pembrolizumab therapy predicts long‑term survival in patients with advanced urothelial carcinoma

Absolute lymphocyte count and C‑reactive protein‑albumin ratio can predict prognosis and adverse events in patients with recurrent esophageal cancer treated with nivolumab therapy

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