Prediction of Soft Tissue Sarcoma from Clinical Characteristics and Laboratory Data

The application of lung immune prognostic index in predicting the prognosis of 302 STS patients

Background

Soft tissue sarcoma (STS) are heterogeneous and rare tumors, and few studies have explored predicting the prognosis of patients with STS. The Lung Immune Prognostic Index (LIPI), calculated based on baseline serum lactate dehydrogenase (LDH) and the derived neutrophils/(leukocytes minus neutrophils) ratio (dNLR), was considered effective in predicting the prognosis of patients with pulmonary cancer and other malignancies. However, the efficacy of the LIPI in predicting the prognosis of patients with STS remains unclear.

Methods

This study retrospectively reviewed patients with STS admitted to our center from January 2016 to January 2021. Their hematological and clinical characteristics were collected and analyzed to construct the LIPI specific to STS. The correlations between various predictive factors and overall survival (OS) were examined using Kaplan-Meier and Cox regression analyses. Independent risk factors for OS were identified using univariate and multivariate analyses. Finally, a LIPI nomogram model for STS was established.

Results

This study enrolled 302 patients with STS, of which 87 (28.9%), 162 (53.6%), and 53 (17.5%) were classified into three LIPI-based categories: good, moderate, and poor, respectively (P < 0.0001). The time-dependent operator curve showed that the LIPI had better prognostic predictive ability than other hematological and clinical characteristics. Univariate and multivariate analyses identified the Fédération Nationale des Centres de Lutte Contre le Cancer grade (FNCLCC/G), tumor size, and LIPI as independent risk factors. Finally, a nomogram was constructed by integrating the significant prognostic factors. Its C-index was 0.72, and the calibration curve indicated that it could accurately predict the three- and five-year OS of patients with STS. The decision and clinical impact curves also indicated that implementing this LIPI-nomogram could significantly benefit patients with STS.

Conclusion

This study explored the efficacy of the LIPI in predicting the prognosis of 302 patients with STS, classifying them into three categories to evaluate the prognosis. It also reconstructed a LIPI-based nomogram to assist clinicians in predicting the three- and five-year OS of patients with STS, potentially enabling timely intervention and customized management.

Establishing biomarkers for soft tissue sarcomas

INTRODUCTION

Soft tissue sarcomas (STS) are a rare and diverse group of tumors. Curative options are limited to localized disease, with surgery being the mainstay. Advanced stages are associated with a poor prognosis. Currently, the prognosis of the patient is based on histological classification and clinical characteristics, with only a few biomarkers having entered clinical practice.

AREAS COVERED

This article covers extensive recent research that has established novel potential biomarkers based on genomics, proteomics, and clinical characteristics. Validating and incorporating these biomarkers into clinical practice can improve prognosis, prediction of recurrence, and treatment response. Relevant literature was collected from PubMed, Scopus, and clinicaltrials.gov databases (November 2023).

EXPERT OPINION

Currently, defining prognostic markers in soft tissue sarcomas remains challenging. More studies are required, especially to personalize treatment through advanced genetic profiling and analysis using individual tumor and patient characteristics.

C‑reactive protein and related predictors in soft tissue sarcoma (Review)

C-reactive protein (CRP) is a useful predictor of poor survival in patients with several types of cancer because inflammation is strongly associated with cancer progression. The production of CRP in hepatocytes appears to be primarily induced at the transcriptional level following the elevation of circulating interleukin-6 (IL-6), which is produced by various cell types, including cancer cells and cancer-associated fibroblasts. Serum CRP levels are associated with serum IL-6 levels in patients with soft tissue sarcoma (STS). Additionally, patients with elevated CRP levels had worse oncological outcomes than those with normal CRP levels. It has been attempted to combine CRP levels with other inflammatory or immune markers, and the utility of this has been demonstrated. Therefore, a novel treatment strategy should be developed for patients with STS with elevated CRP levels. The present review aimed to clarify the role of CRP levels and related tools in predicting clinical outcomes in patients with STS.

Is Lymphocyte C-Reactive Protein Ratio Useful for Predicting Survival in Patients with Non-Metastatic Soft Tissue Sarcoma?

Background: Recently, the lymphocyte-to-CRP ratio (LCR) was found to have a prognostic role in many cancers. However, the clinical significance of LCR in patients with soft tissue sarcoma (STS) has not yet been established. This study aimed to determine whether LCR can predict disease-specific survival (DSS) and event-free survival (EFS) in patients with STS. Methods: In this study, 132 patients were enrolled. The mean follow-up periods were 76.5 months. Blood examinations were performed prior to treatment for all patients. Results: The 5-year DSS in patients with higher and lower LCR was 86.5% and 52.8%, respectively (p < 0.001). Patients with lower LCR had worse survival than those with higher LCR. The 5-year EFS in patients with higher and lower LCR was 66.2% and 31.2%, respectively (p < 0.001). On Receiver operating characteristic analysis, however, there was no significant difference in the area under curve (AUC) between CRP level (AUC = 0.72) and LCR (AUC = 0.711). Conclusions: LCR may be a prognostic factor for predicting oncological events in multivariate analysis, although ROC analysis could not show the superiority of LCR to CRP for predicting oncological outcomes in patients with STS.

Serum lactate dehydrogenase levels predict the prognosis of patients with soft tissue sarcoma

Several studies have reported the prognostic factors for soft tissue sarcoma. Although serum lactate dehydrogenase (LDH) levels are associated with poor prognosis in several types of cancer, their role in soft tissue sarcomas remains unclear. Therefore, the present study evaluated the association between serum LDH levels and the clinical characteristics and prognosis of soft tissue sarcoma. A total of 103 patients diagnosed with primary soft tissue sarcoma between 2003 and 2019 were retrospectively examined, and the association between serum LDH levels at the first visit and clinical characteristics were analysed. In high-grade soft tissue sarcoma, the association between survival and clinical characteristics, including stratified LDH levels, was also analysed. Serum LDH levels were stratified (>253 and ≤253 IU/l) according to the standard values used at our institution. High serum LDH levels were significantly associated with the presence of metastasis and histological grade (P<0.001 and 0.040, respectively). In both the univariate and multivariate analyses, disease-specific survival (DSS) was significantly worse in patients with high-grade soft tissue sarcoma and high serum LDH levels than in patients with normal serum LDH levels (univariate analysis: P=0.025; multivariate analysis: Hazard ratio, 4.60; 95% confidence interval, 1.16-18.2; P=0.030). In conclusion, high serum LDH levels at the first visit predicted the presence of distant metastasis, high histological grade and worse DSS in patients with high-grade soft tissue sarcoma. Therefore, in patients with high serum LDH levels at the first visit, these risks should be considered during pretreatment examinations and post-treatment follow-up.

Hand tumors: A review of 186 patients at a single institute

PURPOSE

The spectrum of diagnoses and clinical features of hand tumors differ from those of tumors in other body parts. However, only a few reports have comprehensively referenced the diagnosis and clinical features of hand tumors. This study aimed to elucidate the diagnostic distribution and the clinical features of hand tumors undergone surgery in our institute.

PATIENTS AND METHODS

A total of 235 lesions in 186 patients diagnosed with hand tumors between 1978 and 2020 were reviewed. Age at surgery, gender, chief complaint, tumor location, and pathological diagnosis were analyzed.

RESULTS

There were 121 benign bone tumors, 98 benign soft tissue tumors, and 16 malignant tumors. Chondroma and tenosynovial giant cell tumor were common benign bone and soft tissue tumors at the proximal phalanx of the ring finger and the palm, respectively. Meanwhile, chondrosarcoma and synovial sarcoma were common malignant tumors at the dorsal part of the hand. Local pain and painless mass were the chief complaints in patients with benign bone and soft tissue tumors, respectively. Most patients with malignant tumors were referred after unplanned resection. When patients were classified into two categories by tumor size according to maximal diameter, tumors larger than 19 mm had a significantly higher risk of malignant (p = 0.031) despite being smaller than other tumors in different body parts.

CONCLUSION

When a tumor malignancy is suspected, the patient should be referred to a specialist to avoid unplanned resection or delayed diagnosis due to misdiagnosis. Knowing the distribution and clinical features should help in diagnosing hand tumors.

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.