The role of radiomics for predicting of lymph-vascular space invasion in cervical cancer patients based on artificial intelligence: a systematic review and meta-analysis.

The primary aim of this study was to conduct a methodical examination and assessment of the prognostic efficacy exhibited by magnetic resonance imaging (MRI)-derived radiomic models concerning the preoperative prediction of lymph-vascular space infiltration (LVSI) in cervical cancer cases. A comprehensive and thorough exploration of pertinent academic literature was undertaken by two investigators, employing the resources of the Embase, PubMed, Web of Science, and Cochrane Library databases. The scope of this research was bounded by a publication cutoff date of May 15, 2023. The inclusion criteria encompassed studies that utilized radiomic models based on MRI to prognosticate the accuracy of preoperative LVSI estimation in instances of cervical cancer. The Diagnostic Accuracy Studies-2 framework and the Radiomic Quality Score metric were employed. This investigation included nine distinct research studies, enrolling a total of 1,406 patients. The diagnostic performance metrics of MRI-based radiomic models in the prediction of preoperative LVSI among cervical cancer patients were determined as follows: sensitivity of 83% (95% confidence interval [CI]=77%-87%), specificity of 74% (95% CI=69%-79%), and a corresponding AUC of summary receiver operating characteristic measuring 0.86 (95% CI=0.82-0.88). The results of the synthesized meta-analysis did not reveal substantial heterogeneity.This meta-analysis suggests the robust diagnostic proficiency of the MRI-based radiomic model in the prognostication of preoperative LVSI within the cohort of cervical cancer patients. In the future, radiomics holds the potential to emerge as a widely applicable noninvasive modality for the early detection of LVSI in the context of cervical cancer.

Predictive significance of lymphocyte level and neutrophil-to-lymphocyte ratio values during radiotherapy in cervical cancer treatment.

OBJECTIVE: The objective of this research was to analyze the prognostic significance of the minimum count of lymphocytes (LY) and the corresponding ratio of neutrophil-to-lymphocyte (NLR) in cervical cancer (CC) patients receiving radiotherapy. METHODS: We retrospectively collected data from 202 CC patients who received concurrent chemoradiotherapy or radiotherapy alone at our hospital. Statistical methods including the Kaplan-Meier method, log-rank test and the Cox proportional hazards model were included to examine survival differences and identify independent factors that may affect overall survival (OS) and progression-free survival (PFS). RESULTS: The research enrolled a total of 202 patients. Patients with higher LY levels and lower NLR values during radiotherapy had significantly better survival prognosis than those with lower LY levels and higher NLR values. Multivariate COX regression analysis revealed that FIGO stage I, pathological types of SqCC, absence of lymph node metastasis, concurrent chemoradiotherapy, higher LY levels during radiotherapy, and lower NLR values before radiotherapy were independently associated with poorer PFS. Similarly, FIGO stage I, absence of lymph node metastasis and lower NLR values during and before radiotherapy were independently linked with poorer OS. CONCLUSION: Minimum LY value and its corresponding NLR during radiotherapy serve as prognostic factors for CC.

Assessment of Peripheral Platelet to Lymphocyte Ratio and Prognostic Nutritional Index in the Efficacy and Prognosis of Radiotherapy for Cervical Cancer.

This study aimed to evaluate the correlation between the pre-treatment peripheral platelet-to-lymphocyte ratio (PLR) and the prognostic nutritional index (PNI) with the efficacy and prognosis of radiotherapy for cervical cancer. A total of 110 patients with cervical cancer who received radiotherapy at our hospital from November 2017 to November 2020 were retrospectively analysed. The cut-off values of PLR and PNI were obtained using the receive operating characteristic curve (ROC) and the Youden index. The patients were divided into high PLR and low PLR and high PNI and low PNI groups. We compared the clinical characteristics, 3-year overall survival (OS), and progression-free survival (PFS) between the high and low PLR groups, as well as the high and low PNI groups of patients. Cox regression was used to analyse the factors influencing OS and PFS. The median follow-up duration was 26 months. The optimal cut-off value for PLR was 186.88 and that for PNI was 47.35. The 3-year OS values were 81.00% and 97.10% for the high PLR (PLR > 186.88) and low PLR (PLR ≤ 186.88) groups, respectively, and the 3-year PFS values were 59.50% and 88.20% for the high PLR and low PLR groups, respectively, with statistically significant differences (p < 0.05). The 3-year OS values were 97.50% and 74.20% for the high PNI (PNI > 47.35) and the low PNI (PNI ≤ 47.35) groups, respectively, and the 3-year PFS values were 87.30% and 51.60% for the high PNI and low PNI groups, respectively, with statistically significant differences (p < 0.05). Multifactorial Cox regression analyses revealed that high PLR value (PLR > 187.88), low PNI value (PNI ≤ 47.35), histological type, and FIGO stage were independent risk factors for the OS of cervical cancer. Pretreatment PNI values and PLR values can be used as simple and feasible predictors of clinical efficacy and prognosis for patients treated with radiotherapy for cervical cancer.