Pretreatment Leukocyte Count Ratios as Metastatic Predictive Factors in Luminal Type Breast Cancer

Wira Wiguna, I Gede Wikania; Indrani Remitha, Ni Putu Sri; Sadvika, I Gusti Ayu Stiti; Wiranata, Sinta; Putra, I Wayan Ardyan Sudharta; Adiputra, Putu Anda Tusta; Supadmanaba, I Gede Putu; Wihandani, Desak Made

doi:10.31557/APJCP.2022.23.5.1595

Pretreatment Leukocyte Count Ratios as Metastatic Predictive Factors in Luminal Type Breast Cancer

Document Type : Research Articles

Authors

¹ Faculty of Medicine, Udayana University, Denpasar, Bali, Indonesia.

² Department of Biochemistry, Faculty of Medicine, Universitas Udayana, Bali, Indonesia.

³ Department of Surgery, Division of Surgical Oncology, Faculty of Medicine, Universitas Udayana, Sanglah General Hospital, Bali Indonesia.

10.31557/APJCP.2022.23.5.1595

Abstract

Objective: Molecular based predictive biomarkers have been developed but still unaffordable in developing countries. The leukocyte ratio is known as a promising, affordable and practical biomarker. However, the evidence to support their application is still lacking, especially from developing countries. Therefore, this study aimed to evaluate the association between leukocytes count ratios as predictive markers of metastasis in luminal type breast cancer. Methods: A retrospective cross-sectional study was conducted using breast cancer patient data obtained at Sanglah General Hospital (2016-2020). Complete blood count (CBC) and histopathological records of the patients were collected and the basophil-to-lymphocyte ratio (BLR), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) were calculated. Tumor stadium was classified into early (I-II) and advance (III-IV) stage while distant metastasis was classified into M0 and M1. Data were then analyzed using ROC curve and then followed by chi square and logistic regression analysis to obtain OR value. Results: Two hundred eighty-three luminal breast cancer patient data were used in this study with mean age 49.27 ± 9.451. Most of the patient had advanced disease (177 patients; 62.5%) while metastatic disease accounted for 54 patients (19.1%) of all patients. Patients with metastatic disease had higher median of BLR, MLR, NLR and PLR (0.043 ± 0.025, p=0.034; 0.289 ± 0.285, p=0.008; 3.489 ± 5.027, p=0.044; 159.538 ± 127.79, p=0.008) than patients without metastasis. The AUC (sensitivity and specificity) of BLR, MLR, NLR and PLR in predicting metastasis were 0.593 (51%; 65%), 0.616 (35%; 89%), 0.588 (46%; 75%) and 0.615 (40%; 81%), respectively. In multivariate risk analysis model, patients with metastasis were found in high BLR (Adjusted OR: 2.045; 95%CI=1.123-3.723; p=0.019), MLR (Adjusted OR: 4.862; 95%CI=2.401-9.844; p<0.001), NLR (Adjusted OR: 2.727; 95%CI=1.475-5.044; p=0.001) and PLR (Adjusted OR: 3.061; 95%CI=1.618-5.792; p=0.001). Conclusion: Pretreatment leukocyte ratios are potential predictive markers for metastasis. However, these findings need to be validated in larger and prospective studies with more comprehensive design.

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