A new score based on biomarker values to predict the prognosis of locally advanced cervical cancer

Pathogenic and Prognostic Roles of Paraneoplastic Leukocytosis in Cervical Cancer: Can Genomic-Based Targeted Therapies Have a Role? A Literature Review and an Emblematic Case Report

Tumor-associated leukocytosis has been associated with poor prognosis in cervical cancer. Leukemoid reaction (i.e., white blood cell count > 40,000/μL) is defined paraneoplastic (PLR) when it occurs in the presence of a cytokine-secreting tumor (CST) without neoplastic bone marrow infiltration. Cervical cancers displaying PLR represent a peculiar entity characterized by a rapidly progressive behavior typically associated with chemo-radioresistance. The present paper aims to review the literature about the pathogenetic mechanisms of PLR and its prognostic role in cervical cancer. Moreover, it reports the emblematic case of a patient with an advanced cervical cancer associated with PLR that was chemotherapy resistant. The patient underwent a palliative cytoreductive surgery of high complexity, obtaining a temporary regression of PLR. The tumor sample stained positive for G-CSF and IL-6, thus indicating a CST. Notably, the tumor genomic analysis revealed a PI3CKA mutation. Therefore, at the instrumental evidence of a rapidly progressive disease relapse, which was accompanied by reappearance of PLR, we started a targeted treatment with a selective PIK3 inhibitor alpesilib combined with the JAK1-2 inhibitor ruxolitinib. We achieved a relief of symptoms and leukocytosis; however, severe side effects necessitated the treatment suspension. In conclusion, as therapeutic strategies for cancer with PLR are scarcely reported in literature, our study could contribute to expand our understanding of the topic and provide a basis for further research.

Machine Learning of Dose-Volume Histogram Parameters Predicting Overall Survival in Patients with Cervical Cancer Treated with Definitive Radiotherapy

Purpose

To analyze the effects of dosimetric parameters and clinical characteristics on overall survival (OS) by machine learning algorithms.

Methods and Materials

128 patients with cervical cancer were treated with definitive pelvic radiotherapy with or without chemotherapy followed by image-guided brachytherapy. The elastic-net models with integrating DVH parameters and baseline clinical factors, only DVH parameters and only baseline clinical factors were constructed in 5-folds cross-validations for 100 iteration bootstrapping, and then were compared using concordance index (C-index) criteria. Finally, the selected important factors were used to build multivariable Cox-pH models for OS and also shown in nomograms for clinical usage.

Results

The median OS occurred was 25.78 months with 25 (19.53%) deaths. The elastic-net models integrating clinical and DVH factors had the best prediction performances (C-index 0.76 in the train set and C-index 0.74 in the test set). Three important factors were selected, including baseline hemoglobin level as the protective factor, primary tumor volume (GTV_P) volume, and body V5 as the risk factors. The final multivariable Cox-pH models were constructed using these important factors and had prediction performance (C-index: 0.78, 95%CI: 0.73–0.81).

Conclusions

This is the first attempt to establish elastic-net models to study the contributions of DVH parameters for predicting OS in patients with cervical cancer. These results can facilitate individualized tailoring of radiation treatment in cervical cancer patients.

Evaluation of prognostic factors after primary chemoradiotherapy of anal cancer: A multicenter study of the German Cancer Consortium-Radiation Oncology Group (DKTK-ROG)

BACKGROUND AND PURPOSE

Prognosis after chemoradiotherapy (CRT) for anal squamous cell carcinoma (ASCC) shows marked differences among patients according to TNM subgroups, however individualized risk assessment tools to better stratify patients for treatment (de-) escalation or intensified follow-up are lacking in ASCC.

MATERIALS AND METHODS

Patients' data from eight sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG), comprising a total of 605 patients with ASCC, treated with standard definitive CRT with 5-FU/Mitomycin C or Capecitabine/Mitomycin C between 2004-2018, were used to evaluate prognostic factors based on Cox regression models for disease-free survival (DFS). Evaluated variables included age, gender, Karnofsky performance score (KPS), HIV-status, T-category, lymph node status and laboratory parameters. Multivariate cox models were separately constructed for the whole cohort and the subset of patients with early-stage (cT1-2 N0M0) tumors.

RESULTS

After a median follow-up of 46 months, 3-year DFS for patients with early-stage ASCC was 84.9%, and 67.1% for patients with locally-advanced disease (HR 2.4, p < 0.001). T-category (HR vs. T1: T2 2.02; T3 2.11; T4 3.03), N-category (HR versus N0: 1.8 for N1-3), age (HR 1.02 per year), and KPS (HR 0.8 per step) were significant predictors for DFS in multivariate analysis in the entire cohort. The model performed with a C-index of 0.68. In cT1-2N0 patients, T-category (HR 2.14), HIV status (HR 2.57), age (1.026 per year), KPS (HR 0.7 per step) and elevated platelets (HR 1.3 per 100/nl) were associated with worse DFS (C-index of 0.7).

CONCLUSION

Classical clinicopathologic parameters like T-category, N-category, age and KPS remain to be significant prognostic factors for DFS in patients treated with contemporary CRT for ASCC. HIV and platelets were significantly associated with worse DFS in patients with early stage ASCC.