The Predictive Value of Neutrophil-to-Lymphocyte Ratio for Hodgkin's Lymphoma Diagnosis in Patients with Asymptomatic Cervical Lymphadenopathy

Machine Learning Logistic Regression Model for Early Decision Making in Referral of Children with Cervical Lymphadenopathy Suspected of Lymphoma

While cervical lymphadenopathy is common in children, a decision model for detecting high-grade lymphoma is lacking. Previously reported individual lymphoma-predicting factors and multivariate models were not sufficiently discriminative for clinical application. To develop a diagnostic scoring tool, we collected data from all children with cervical lymphadenopathy referred to our national pediatric oncology center within 30 months (n = 182). Thirty-nine putative lymphoma-predictive factors were investigated. The outcome groups were classical Hodgkin lymphoma (cHL), nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL), non-Hodgkin lymphoma (NHL), other malignancies, and a benign group. We integrated the best univariate predicting factors into a multivariate, machine learning model. Logistic regression allocated each variable a weighing factor. The model was tested in a different patient cohort (n = 60). We report a 12-factor diagnostic model with a sensitivity of 95% (95% CI 89-98%) and a specificity of 88% (95% CI 77-94%) for detecting cHL and NHL. Our 12-factor diagnostic scoring model is highly sensitive and specific in detecting high-grade lymphomas in children with cervical lymphadenopathy. It may enable fast referral to a pediatric oncologist in patients with high-grade lymphoma and may reduce the number of referrals and unnecessary invasive procedures in children with benign lymphadenopathy.

Preoperative Blood Inflammatory Markers for the Differentiation of Uterine Leiomyosarcoma from Leiomyoma

Purpose

Preoperative diagnosis of uterine leiomyosarcoma (LMS) is challenging because the disease can mimic benign leiomyoma (LM). The objective of the present study was to investigate the role of preoperative clinical characteristics and hematologic parameters to differentiate uterine LMS and LM.

Methods

Preoperative clinical and laboratory variables were reviewed retrospectively in patients with LMS or LM, and the significances of intergroup differences were assessed. Receiver operating characteristic (ROC) curves were used to determine optimal cut-off values for each variable. Logistic regression analysis was applied to identify variables predicting the presence of LMS.

Results

The preoperative clinical and laboratory variables of 336 patients with uterine tumor were analyzed. Seventy-nine patients had LMS and 257 had LM. A significant difference was observed between LMS and LM in terms of the median value of age at diagnosis, menopausal status, white blood cell (WBC) count, absolute neutrophil count (ANC), C-reactive protein (CRP), lactate dehydrogenase (LDH), and neutrophil-to-lymphocyte ratio (NLR) (all P < 0.001). Multivariate analyses showed that menopausal status (odds ratio [OR] = 3.40, P= 0.002), WBC count (OR = 2.09, P = 0.012), ANC (OR = 3.17, P < 0.001), CRP (OR = 21.74, P < 0.001), LDH (OR = 10.77, P < 0.001), and NLR (OR = 2.58, P = 0.001) predicted the presence of LMS.

Conclusion

Our results suggest that in older or postmenopausal patients, high WBC count, ANC, CRP, LDH, and NLR could be useful biomarkers for the differentiation of LMS and LM, which indicate that serum markers might be useful, cost-effective, and broadly available diagnostic markers for uterine LMS.

Evaluation of the predictive role of neutrophil/lymphocyte ratio in the diagnosis of lymphoma in patients with asymptomatic and ısolated cervical lymphadenopathy

Introduction

The diagnostic approach to patients with isolated asymptomatic cervical lymphadenopathy varies between excisional biopsy and follow-up. When the anamnesis, physical examination, laboratory and imaging findings are not sufficient to identify the etiology, an excisional biopsy is performed for the differential diagnosis between early-stage lymphoma and infectious or reactive causes. If the excisional biopsy, which may have some complications, is not performed, it may delay the diagnosis of lymphoma. This diagnostic challenge could be avoided by predictive markers.

Objectives

This study was planned to determine the predictive value of neutrophil/lymphocyte ratio in the diagnosis of Hodgkin and non-Hodgkin limphoma in patients with asymptomatic, isolated cervical limphadenopathy and underwent excisional biopsy.

Methods

A total of 90 patients between the years 2016 − 2019 admitted to our clinics due to asymptomatic isolated cervical lymphadenopathy, present in at least 4 weeks with lympho nodes in pathological dimensions persisting in the cervical region, were included to our study. An excisional lympho node biopsy was performed in all 90 patients.

Results

Of the 90 patients who underwent excisional biopsy; 34 were diagnosed as reactive lymphadenopathy 30 were non-Hodgkin linphoma, and 26 were Hodgkin linphoma. A total of 56 (62.2%) patients were diagnosed as lymphoma, either Hodgkin or non-Hodgkin, while 34 patients (38.8%) were diagnosed as reactive lymphadenopathy. The median age, total whiteblood count, neutrophil count of the lymphoma groups were significantly higher than reactive lymphadenopathy group, whereas the lymphocyte count was significantly lower in the lymphoma patients. The median neutrophil/ lymphocyte ratio was 1.7 in the reactive lymphadenopathy group, 3.5 in the non-Hodgkin limphoma group, and 3.0 in the Hodgkin limphoma group (p <  0.001).

Conclusion

According to the results of our study, neutrophil/lymphocyte ratio was significantly higher in patients who were admitted with isolated asymptomatic lymphadenopathy and were diagnosed with lymphoma, and who were diagnosed with early-stage Hodgkin and non- Hodgkin lymphoma compared to those who were found to have reactive lymphadenopathy. Neutrophil/lymphocyte ratio, which is a low-cost, fast and easy-to-access test, has a predictive value in the diagnosis of lymphoma in patients with asymptomatic lymphadenopathy.