Is there an association between lymph node size and hyperprogression in immunotherapy-treated patients?

BACKGROUND: Hyperprogressive disease (HPD) can be described as an accelerated increase in the growth rate of tumors combined with rapid clinical deterioration observed in a subset of cancer patients undergoing immunotherapy, specifically with immune checkpoint inhibitors (ICIs). The reported incidence of HPD ranges from 5.9% to 43.1% in patients receiving ICIs. In this context, identifying reliable predictive risk factors for HPD is crucial as it may allow for earlier intervention and ultimately improve patient outcomes. METHODS: This study retrospectively analyzed ten metastatic renal cell carcinoma (mRCC) patients. The identification of HPD was based on the diagnostic criteria proposed by Ferrara R et al. This study aimed to investigate whether there is an association between LN size and HPD using a cutoff value of 3 cm for LN size. Given the limited sample size, Fisher's exact test was used to test this association. We conducted a Kaplan-Meier (KM) analysis to estimate the median overall survival (OS) of patients with HPD and compared it to those without HPD. RESULTS: Three patients (30%) developed HPD, while seven (70%) did not. Fisher's exact test revealed a statistically significant association between the HPD and LN size ≥ 3 cm (p=0.008). In the HPD group, the median OS was significantly shorter, with a median OS of 3 months, whereas in the non-HPD group, the median OS was not reached (P =0.001). CONCLUSION: The present study found a significant association between LN size ≥ 3 cm in the pretreatment period and HPD development.

Impact of KRAS Mutation on Survival Outcome of Patients With Metastatic Colorectal Cancer in Jordan.

Background Colorectal cancer (CRC) is the most prevalent cancer in males, with an incidence rate (IR) of 13.1%, and the second most prevalent cancer in females, with an IR of 8.4%, coming after breast cancer in Jordan. The present study was motivated by conflicting clinical data regarding the prognostic impact of Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in patients with metastatic colorectal cancer (mCRC). Our study aimed to investigate if KRAS mutation conferred a negative prognostic value in Jordanian patients with mCRC. Materials and methods The current study is a retrospective study that collected data from a cohort of 135 mCRC patients diagnosed between 1 January 2017 and 1 January 2022 at our Oncology Department at the Jordanian Military Cancer Center (MCAC) using our patients' electronic medical records. The last follow-up date was 1 September 2022. From the cohort, we obtained data regarding age, sex, date of diagnosis, metastatic spread, KRAS status, either mutated KRAS or wild-type KRAS, and location of the primary tumor. All patients underwent tumor tissue biopsies to determine KRAS mutational status based on quantitative polymerase chain reaction and reverse hybridization from an accredited diagnostic laboratory at Jordan University Hospital. Statistical analysis was carried out to address the associations between KRAS mutation and the patients-tumor characteristics and their prognosis on survival. Results KRAS mutation was found in 40.3% of the participants in the study, and 56.7% had the wild type. There was a predilection of KRAS mutation, with 67% on the right side versus 33% on the left side (p = 0.018). Kaplan-Meier survival analysis showed worse survival outcomes in KRAS mutant patients (p = 0.002). The median overall survival in the KRAS mutant patients was 17 months (95% confidence interval (CI): 13.762-19.273) compared to 21 months (95% CI: 20.507-27.648) in patients with wild-type KRAS. Additionally, the Cox regression model identified that KRAS mutation carries a poorer prognosis on survival outcome hazard ratio (HR: 2.045, 95% CI: 1.291-3.237, p = 0.002). The test also showed statistical significance in the metastatic site (lung only). But this time, it was associated with a better survival outcome (HR: 0.383, 95% CI: 0.186-0.788, p = 0.009). Conclusion The present study shows that the presence of KRAS mutation has been found to negatively impact the prognosis and survival outcome of Jordanian patients with mCRC.

Application of Artificial Neural Network to Preoperative 18F-FDG PET/CT for Predicting Pathological Nodal Involvement in Non-small-cell Lung Cancer Patients.

Purpose: To evaluate the performance of artificial neural networks (aNN) applied to preoperative 18F-FDG PET/CT for predicting nodal involvement in non-small-cell lung cancer (NSCLC) patients. Methods: We retrospectively analyzed data from 540 clinically resectable NSCLC patients (333 M; 67.4 ± 9 years) undergone preoperative 18F-FDG PET/CT and pulmonary resection with hilo-mediastinal lymphadenectomy. A 3-layers NN model was applied (dataset randomly splitted into 2/3 training and 1/3 testing). Using histopathological reference standard, NN performance for nodal involvement (N0/N+ patient) was calculated by ROC analysis in terms of: area under the curve (AUC), accuracy (ACC), sensitivity (SE), specificity (SP), positive and negative predictive values (PPV, NPV). Diagnostic performance of PET visual analysis (N+ patient: at least one node with uptake ≥ mediastinal blood-pool) and of logistic regression (LR) was evaluated. Results: Histology proved 108/540 (20%) nodal-metastatic patients. Among all collected data, relevant features selected as input parameters were: patients' age, tumor parameters (size, PET visual and semiquantitative features, histotype, grading), PET visual nodal result (patient-based, as N0/N+ and N0/N1/N2). Training and testing NN performance (AUC = 0.849, 0.769): ACC = 80 and 77%; SE = 72 and 58%; SP = 81 and 81%; PPV = 50 and 44%; NPV = 92 and 89%, respectively. Visual PET performance: ACC = 82%, SE = 32%, SP = 94%; PPV = 57%, NPV = 85%. Training and testing LR performance (AUC = 0.795, 0.763): ACC = 75 and 77%; SE = 68 and 55%; SP = 77 and 82%; PPV = 43 and 43%; NPV = 90 and 88%, respectively. Conclusions: aNN application to preoperative 18F-FDG PET/CT provides overall good performance for predicting nodal involvement in NSCLC patients candidate to surgery, especially for ruling out nodal metastases, being NPV the best diagnostic result; a high NPV was also reached by PET qualitative assessment. Moreover, in such population with low a priori nodal involvement probability, aNN better identify the relatively few and unexpected nodal-metastatic patients than PET analysis, so supporting the additional aNN use in case of PET-negative images.