The prognostic power of inflammatory indices and clinical factors in metastatic castration-resistant prostate cancer patients treated with radium-223 (BIO-Ra study).

PURPOSE: To combine peripheral blood indices and clinical factors in a prognostic score for metastatic castration-resistant prostate cancer (mCRPC) patients treated with radium-223 dichloride ([223Ra]RaCl2). PATIENTS AND METHODS: Baseline neutrophil-to-lymphocyte ratio (NLR), derived NLR (donor), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic inflammation index (SII), Eastern Cooperative Oncology Group performance status (ECOG PS), Gleason score (GS) group, number of bone metastases, prostate-specific antigen (PSA), alkaline phosphatase (ALP), line of therapy, previous chemotherapy, and the presence of lymphadenopathies were collected from seven Italian centers between 2013 and 2020. Lab and clinical data were assessed in correlation with the overall survival (OS). Inflammatory indices were then included separately in the multivariable analyses with the prognostic clinical factors. The model with the highest discriminative ability (c-index) was chosen to develop the BIO-Ra score. RESULTS: Five hundred and nineteen mCRPC patients (median OS: 19.9 months) were enrolled. Higher NLR, dNLR, PLR, and SII and lower LMR predicted worse OS (all with a p < 0.001). The multivariable model including NLR, ECOG PS, number of bone metastases, ALP, and PSA (c-index: 0.724) was chosen to develop the BIO-Ra score. Using the Schneeweiss scoring system, the BIO-Ra score identified three prognostic groups (36%, 27.3%, and 36.6% patients, respectively) with distinct median OS (31, 26.6, and 9.6 months, respectively; hazard ratio: 1.62, p = 0.008 for group 2 vs. 1 and 5.77, p < 0.001 for group 3 vs. 1). CONCLUSIONS: The BIO-Ra score represents an easy and widely applicable tool for the prognostic stratification of mCRPC patients treated with [223Ra]RaCl2 with no additional costs.

Sarcopenic Obesity in Cervical Carcinoma: A Strong and Independent Prognostic Factor beyond the Conventional Predictors (ESTHER Study-AFRAID Project).

Locally advanced cervical cancer represents a significant treatment challenge. Body composition parameters such as body mass index, sarcopenia, and sarcopenic obesity, defined by sarcopenia and BMI ≥ 30 kg/m2, have been identified as potential prognostic factors, yet their overall impact remains underexplored. This study assessed the relationship between these anthropometric parameters alongside clinical prognostic factors on the prognosis of 173 cervical cancer patients. Survival outcomes in terms of local control (LC), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were analyzed using Kaplan regression methods-Meier and Cox. Older age, lower hemoglobin levels, higher FIGO (International Federation of Gynecology and Obstetrics) stages, and lower total radiation doses were significantly associated with worse outcomes. Univariate analysis showed a significant correlation between BMI and the outcomes examined, revealing that normal-weight patients show higher survival rates, which was not confirmed by the multivariate analysis. Sarcopenia was not correlated with any of the outcomes considered, while sarcopenic obesity was identified as an independent negative predictor of DFS (HR: 5.289, 95% CI: 1.298-21.546, p = 0.020) and OS (HR: 2.645, 95% CI: 1.275-5.488, p = 0.009). This study highlights the potential of sarcopenic obesity as an independent predictor of clinical outcomes. These results support their inclusion in prognostic assessments and treatment planning for patients with advanced cervical cancer.

Decoding the Complexity of Systemic Inflammation Predictors in Locally Advanced Cervical Cancer, with Hemoglobin as the Hidden Key (the ESTHER Study).

Locally advanced cervical cancer (LACC) is treated with concurrent chemoradiation (CRT). Predictive models could improve the outcome through treatment personalization. Several factors influence prognosis in LACC, but the role of systemic inflammation indices (IIs) is unclear. This study aims to assess the correlation between IIs and prognosis in a large patient cohort considering several clinical data. We retrospectively analyzed pretreatment IIs (NLR, PLR, MLR, SII, LLR, COP-NLR, APRI, ALRI, SIRI, and ANRI) in 173 LACC patients. Patient, tumor, and treatment characteristics were also considered. Univariate and multivariate Cox's regressions were conducted to assess associations between IIs and clinical factors with local control (LC), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS). Univariate analysis showed significant correlations between age, HB levels, tumor stage, FIGO stage, and CRT dose with survival outcomes. Specific pretreatment IIs (NLR, PLR, APRI, ANRI, and COP-NLR) demonstrated associations only with LC. The multivariate analysis confirmed Hb levels, CRT dose, and age as significant predictors of OS, while no II was correlated with any clinical outcome. The study findings contradict some prior research on IIs in LACC, emphasizing the need for comprehensive assessments of potential confounding variables.

Classical Prognostic Factors Predict Prognosis Better than Inflammatory Indices in Locally Advanced Cervical Cancer: Results of a Comprehensive Observational Study including Tumor-, Patient-, and Treatment-Related Data (ESTHER Study).

Systemic inflammation indices were found to be correlated with therapeutic outcome in several cancers. This study retrospectively analyzes the predictive role of a broad range of systemic inflammatory markers in patients with locally advanced cervical cancer (LACC) including patient-, tumor-, and treatment-related potential prognostic factors. All patients underwent definitive chemoradiation and pretreatment values of several inflammatory indices (neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio, monocyte/lymphocyte ratio, systemic immune inflammation index (SII), leukocyte/lymphocyte ratio, combination of platelet count and NLR, aspartate aminotransferase/platelet ratio index, aspartate aminotransferase/lymphocyte ratio index, systemic inflammatory response index, and aspartate transaminase/neutrophil ratio index) were calculated. Their correlation with local control (LC), distant metastasis-free (DMFS), disease-free (DFS), and overall survival (OS) was analyzed. One hundred and seventy-three patients were included. At multivariable analysis significant correlations were recorded among clinical outcomes and older age, advanced FIGO stage, lower hemoglobin levels, larger tumor size, and higher body mass index values. The multivariate analysis showed only the significant correlation between higher SII values and lower DMFS rates (p < 0.01). Our analysis showed no significant correlation between indices and DSF or OS. Further studies are needed to clarify the role of inflammation indices as candidates for inclusion in predictive models in this clinical setting.

How smart is artificial intelligence in organs delineation? Testing a CE and FDA-approved Deep-Learning tool using multiple expert contours delineated on planning CT images.

Background: A CE- and FDA-approved cloud-based Deep learning (DL)-tool for automatic organs at risk (OARs) and clinical target volumes segmentation on computer tomography images is available. Before its implementation in the clinical practice, an independent external validation was conducted. Methods: At least a senior and two in training Radiation Oncologists (ROs) manually contoured the volumes of interest (VOIs) for 6 tumoral sites. The auto-segmented contours were retrieved from the DL-tool and, if needed, manually corrected by ROs. The level of ROs satisfaction and the duration of contouring were registered. Relative volume differences, similarity indices, satisfactory grades, and time saved were analyzed using a semi-automatic tool. Results: Seven thousand seven hundred sixty-five VOIs were delineated on the CT images of 111 representative patients. The median (range) time for manual VOIs delineation, DL-based segmentation, and subsequent manual corrections were 25.0 (8.0-115.0), 2.3 (1.2-8) and 10.0 minutes (0.3-46.3), respectively. The overall time for VOIs retrieving and modification was statistically significantly lower than for manual contouring (p<0.001). The DL-tool was generally appreciated by ROs, with 44% of vote 4 (well done) and 43% of vote 5 (very well done), correlated with the saved time (p<0.001). The relative volume differences and similarity indexes suggested a better inter-agreement of manually adjusted DL-based VOIs than manually segmented ones. Conclusions: The application of the DL-tool resulted satisfactory, especially in complex delineation cases, improving the ROs inter-agreement of delineated VOIs and saving time.

Prevalence of uterine rupture among women with one prior low transverse cesarean and women with unscarred uterus undergoing labor induction with PGE2: A systematic review and meta-analysis.

BACKGROUND: As uterine rupture may affect as many as 11/1000 women with 1 prior cesarean birth and 5/10.000 women with unscarred uterus undergoing labor induction, we intended to estimate the prevalence of such rare outcome when PGE2 is used for cervical ripening and labor induction. METHODS: We searched MEDLINE, ClinicalTrials.gov and the Cochrane library up to September 1st 2020. Retrospective and prospective cohort studies, as well as randomized controlled trials (RCTs) on singleton viable pregnancies receiving PGE2 for cervical ripening and labor induction were reviewed. Prevalence of uterine rupture was meta-analyzed with Freeman-Tukey double arcsine transformation among women with 1 prior low transverse cesarean section and women with unscarred uterus. RESULTS: We reviewed 956 full text articles to include 69 studies. The pooled prevalence rate of uterine rupture is estimated to range between 2 and 9 out of 1000 women with 1 prior low transverse cesarean (5/1000; 95%CI 2-9/1000, 122/9000). The prevalence of uterine rupture among women with unscarred uterus is extremely low, reaching at most 0.7/100.000 (<1/100.000.000; 95%CI <1/100.000.000-0.7/100.000, 8/17.684). CONCLUSIONS: Uterine rupture is a rare event during cervical ripening and labor induction with PGE2.