Rank Statistics Research Articles

Low serum double-stranded DNA levels are associated with higher survival rates in severe COPD patients.

Damage-associated molecular patterns (DAMPs) are endogenous danger signals that alert and activate the immune system upon cellular damage or death. It has previously been shown that DAMP release is increased in patients with COPD, leading to higher levels in extracellular fluids such as serum. In the current study we investigated whether the serum levels of DAMPs were associated with survival rates in COPD patients. A panel of seven DAMPs, consisting of HMGB1, fibrinogen, α-defensin, heat shock protein 70, S100A8, galectin-9 and double-stranded DNA (dsDNA), was measured in serum of 949 severe COPD patients. Maximally selected rank statistics was used to define cut-off values and a Cox proportional hazards model was used to evaluate the effect of high or low DAMP levels on 4-year survival. For DAMPs that were found to affect survival significantly, baseline characteristics were compared between the two DAMP groups. Out of the seven DAMPs, only dsDNA was significantly associated with 4-year survival. Patients with elevated serum level of dsDNA had higher 4-year mortality rates, lower FEV1 % predicted values and higher emphysema scores. In conclusion, in a clinical cohort of 949 patients with moderate-to-severe COPD, elevated serum levels of dsDNA were associated with a higher risk of death. This study further illustrates the potential role of circulating DAMPs, such as dsDNA, in the progression of COPD. Together, the results of this study suggest that levels of circulating dsDNA might serve as an additional prognostic biomarker for survival in COPD patients.

Preprocedural atrial fibrillation burden is associated with recurrence in patients undergoing atrial fibrillation ablation: findings from the ISOLATION AF Ablation Cohort Study

Abstract Background Non-invasive quantification of electrophysiological properties of the atria is increasingly used for outcome prediction in atrial fibrillation (AF) patients. Data on the benefit of the current classification of AF compared to AF burden based on single lead ECG measurements to predict AF recurrences are scarce. Objective This study sought to assess the predictive performance of low versus high AF burden compared to the conventional AF classification for predicting recurrences after AF catheter ablation. Methods A cross-sectional analysis was conducted in AF patients scheduled for catheter ablation included in the prospective multicenter ISOLATION cohort study between July 2020 and November 2022. Clinical characteristics, routine tests, blood tests and rhythm monitoring through single lead ECGs were collected prior to ablation. ECGs were recorded three times daily for four weeks, with additional measurements in case of the onset or relief of symptoms. The primary endpoint was "ablation success" defined as freedom from documented arrhythmia after the blanking period. Of 650 included patients, pre-procedural rhythm monitoring was available in 580. 261 patients had at least 14 days of ECG measurements and completed 12 months of follow-up. In these patients, we compared the recurrences after 12 months between paroxysmal and persistent AF and high versus low AF burden through survival analysis. Maximally selected rank statistics were used to determine the best cut-off value for AF burden. Results In 261 patients, the mean age was 64 ± 9 years, and 33.7% were female. Physicians classified 170 patients (65.1%) as paroxysmal AF and 91 (34.9%) as persistent AF based on medical history. The AF burden is shown in Figure 1. The optimal calculated cut-off value for AF burden was 42%. Out of 170 patients with paroxysmal AF, 17 (10%) had a burden of > 42%. Of the 91 patients with persistent AF, 35 (38%) had a burden of < 42%. After 12 months, a significant difference in recurrences was observed between patients with paroxysmal AF versus persistent AF (p= 0.015). Patients with high AF burden, had more recurrences after 12 months, than patients with a low AF burden (p= 0.006) (Figure 2). Conclusion Our preliminary results suggest that the addition of a new classification of AF based on burden might provide additional benefit in predicting AF recurrences after catheter ablation compared to the current existing classification and may improve prognostication. Completion of patient follow-up is necessary to determine the predictive value of AF burden derived from single lead ECGs for the prediction of AF recurrence.Figure 2.

“Percentage” and “size” of residual viable tumor in lymph node, the performance in estimating pathologic response of lymph node in non-small cell lung cancer treated with neoadjuvant chemoimmunotherapy

There is no universally accepted method for evaluating lymph node metastasis (LNM) in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy. Different protocols recommend evaluating the percentage of residual viable tumor (RVT%) and metastatic tumor size (MTS). Our aim was to determine the prognostic significance of RVT% and MTS, and identify the more effective parameter for pathological evaluating LNM. Two independent cohorts were collected (derivation, n = 84; external validation, n = 42). All patients exhibited metastatic cancer or treatment response in lymph nodes post-surgery. In the derivation cohort, we assessed the mean and largest values of MTS and RVT% in LNM, estimating their optimal cutoffs for event-free survival (EFS) using maximally selected rank statistics. Validation was subsequently conducted in the external validation cohort. The quality of prognostic factors was evaluated using the Area Under Curve (AUC). A positive association was identified between RVT% and MTS, but an absolute association could not be conclusively established. In the derivation cohort, neither the largest MTS (cutoff = 6 mm, p = 0.28), largest RVT% (cutoff = 75%, p = 0.23), nor mean RVT% (cutoff = 55%, p = 0.06) were associated with EFS. However, mean MTS (cutoff = 4.5 mm) in lymph nodes was statistically associated with EFS (p = 0.018), validated by the external cohort (p = 0.017). The prognostic value of MTS exceeded that of ypN staging in both cohorts, as evidenced by higher AUC values. The mean value of MTS can effectively serve as a parameter for the pathological evaluation of lymph nodes, with a threshold of 4.5 mm, closely linked to EFS. Its prognostic value outperforms that of ypN staging.

ОЦЕНКА СТАБИЛЬНОСТИ УРОЖАЙНОСТИ ЯРОВОГО ЯЧМЕНЯ

The purpose of research is to determine the share of influence of factors in the overall variability of barley yield and assess stability using parametric and non-parametric statistical methods in the conditions of the south of the Moscow Region. According to the results of the study (2020–2022), significant contributions to yield variability were identified: environmental conditions – 81.9 %; genotypic characteristics – 7.4 and genotype × environment interaction – 8.2 %. 7 samples (280.7–345.2 g/m2) were classified as excee¬ding the standard. Evaluation by parametric (bi – regression coefficient; S2dᵢ – deviation from regression; θi – average variance component; θ(i) – GE variance component; Wi2 – environmental valence; σi2 – stability variance; CV – coefficient of variation) and nonparametric (S(1,2,3,6) – rank statistics; NP(i) – non-parametric stability statistics; KR – rank sum) stability indicators allowed us to identify differences in the response of the sample under study to environmental conditions. A high correlation was noted between S(3) and NP(4) (r = 0,90), S(1) and S(2) (r = 0,96), S(6) and NP(4) (r = 0,98), Wi2 and σi2, (r = 1,00), Wᵢ2 and θᵢ (r = 1,00), σ2ᵢ and θᵢ (r = 1,00), Wᵢ2 and θ(i) (r = –1,00), σ2ᵢ, and θ(i) (r = –1,00), θᵢ and θ(i) (r = –1,00). Relationship with productivity in such indicators as S(1), S(2), S(3), NP(1), Wᵢ2, σ2ᵢ, S2dᵢ, CV, θᵢ, θ(ᵢ) was weak, the greatest association was noted with bᵢ (r = 0,60), NP(3) (r = –0,67), NP(4) (r = –0,67), S(6) (r = –0,69), KR (r = –0,71), NP(2) (r = –0,78). Samples with a combination of stability and high yield were identified: Alei (k-31363, Russia), Maximus (k-31366, Russia), Austris (k-31368, Latvia), Povolzhsky Luch (k-31392, Russia).

Assessment of Post-Covid-19 Hand Hygiene Compliance Among Nigeria Certificate in Education Biology Students in Zaria, Nigeria

This study titled Assessment of post-COVID-19 hand hygiene compliance among Nigeria Certificate in Education Biology Students in Zaria, Nigeria was a cross-sectional survey work. The study was guided by three research questions and three research objectives. Three hundred forty-six (346) NCE biology students were chosen at random from a population of three thousand four hundred and forty-one using the random sampling technique. The data collection instrument was a structured questionnaire titled "Students Hand-Hygiene Compliance Questionnaire (SHCQ)" which underwent validation by two science education experts from Ahmadu Bello University, Zaria. Split-half method was adopted to determine reliability which gave the reliability coefficient value of 0.77 with Spearman rank statistics. The researchers administered the instrument to respondents over two weeks. The mean and standard deviation were used to analyse the gathered data. According to the results, the College established hand hygiene compliance during the COVID-19 era (X = 4.00, S.D. = 1.20); NCE Biology students in Zaria had low levels of post-COVID-19 hand hygiene compliance (X = 2.80, S.D. = 1.02); and there weren't many obstacles to post-COVID-19 hand hygiene compliance (X = 3.74, S.D. = 1.08). Recommendations among others include: the College management should continue to prioritize and reinforce a robust infrastructure for handwashing facilities, ensure the availability of soap and sanitizers, and conduct regular educational campaigns on proper hand hygiene practices.

Abstract PO2-01-14: Development of Artificial Intelligence-based Machine Learning Models for Predicting Survival In Hormone-Receptor-Positive/HER2-Negative Early Breast Cancer undergoing Neoadjuvant Chemotherapy

Abstract Background. In hormone-receptor positive (HoR)/HER2 negative early breast cancer (BC) multiple efforts have been made to predict disease recurrence and survival. Machine learning techniques have been used but few studies have looked into their applicability in predicting survival on the basis of clinico-pathological characteristics. The aim of this study was to evaluate a random survival forest model to predict the prognosis of this specific BC subtype. Methods. In this multicenter, retrospective study, patients who fulfilled the following inclusion criteria were included: (1) diagnosis of pathologically confirmed HoR-positive/HER2-negative invasive BC; (2) early or locally advanced, stage I-II-III (3) patients receiving neoadjuvant anthracycline and/or taxane-based chemotherapy, concurrently or sequentially; (4) patients undergoing surgery for primary BC. Survival endpoints were disease-free survival (DFS) and overall survival (OS). A random survival forest algorithm was used to develop the predictive model. Ten-fold cross-validation was performed. The C-index and the continuous rank probability score (CRPS) were used to evaluate the discrimination of the predictive model, and a ROC curve was used to evaluate model precision. A cut point analysis based on maximally selected rank statistics was conducted to evaluate the best cut-off in the out-of-bag (OOB) mortality that could maximize DFS and OS prediction. Variable importance was assessed using Breiman-Cutler permutation importance. Results. Overall, 572 patients with HoR-positive/HER2-negative early BC were included. At univariate analysis age, T stage, N stage, grading, ER, PR and Ki67 were found to be significantly associated with DFS and ER, PgR, HER2, pCR ypT and ypN retained statistical significance at multivariate analysis. ER, pCR, pathological T and N stage were found to be significantly associated with OS at univariate and multivariate analysis. The following variables were included in the final model: menopausal status, age, histology, grade, clinical T/N, ER/PgR, Ki67 and HER2, pathological complete response (pCR), ypT and ypN. For DFS, the cross-validated C-index was 0.68 (95% CI 0.63-0.73) and the OOB CRPS was 0.15, with a OOB performance error of 0.31. The AUC calculated at 60 months was 0.91 (95% CI 0.88-0.94). Out-of bag RSF-based risk scores for individual patients were calculated and an optimal cut-off of 22.58 was identified. The HR between high risk and low risk group was 3.08 (95% CI 2.16-4.39, p< 0.001). For OS, the cross-validated C-index was 0.66 (95% CI 0.60-0.71) and the OOB CRPS was 0.17, with a OOB performance error of 0.35. The AUC calculated at 60 months 0.91 (95% CI 0.88-0.95). An optimal cut-off of 21.54 was identified and the HR between low risk and high risk group was 2.50 (95% CI 1.73-3.61, p< 0.001). For DFS, the most important variables were cN (9.00), ypN (7.35), ER (7.21), ypT (5.38), PgR (4.11), pCR (4.01) and age (2.82) while for OS the most important variables were cN (7.88), ER (5.37), PgR (3.61), age (3.37), pCR (2.80), ypT (2.64) and ypN (2.60). Discussion. We analyzed the performance of RSF in the prediction of DFS and OS based on the contribution of clinico-pathological features commonly available at the baseline of the NCT and post-surgery. By selecting patients with HoR-positive HER2-negative disease, we were able to show which clinico-pathological features within a ML model have greater predictive importance. The model could be integrated with image-based tumor and radiology features to improve its predictive accuracy. This retrospective multicenter study suggests that the combination of easily accessible clinico-pathological features within a ML model may reliably predict DFS and OS in the context of HoR-positive/HER2-negative BCs. Citation Format: Luca Mastrantoni, Giovanna Garufi, Noemi Maliziola, Elena Di Monte, Giorgia Arcuri, Valentina Frescura, Angelachiara Rotondi, Giulia Giordano, Luisa Carbognin, Alessandra Fabi, Ida Paris, Gianluca Franceschini, Armando Orlandi, Antonella Palazzo, Giovanni Scambia, Giampaolo Tortora, Emilio Bria. Development of Artificial Intelligence-based Machine Learning Models for Predicting Survival In Hormone-Receptor-Positive/HER2-Negative Early Breast Cancer undergoing Neoadjuvant Chemotherapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-01-14.

Abstract PO3-14-06: Immunologic features and association with prognosis in hormone receptor-positive/HER2-negative (HR+/HER2-) metastatic breast cancer (MBC) treated with chemotherapy (CT) or CDK4/6-inhibitors (CDK4/6i) + endocrine therapy (ET)

Abstract Purpose: Little is known regarding the prognostic and predictive role of tumor immunological features in HR+/HER2- MBC treated with CT or CDK4/6i+ET. Methods: The Italian KENDO phase 2 trial randomized CT-naïve patients with HR+/HER2-neg. MBC with aggressive characteristics to receive CDK4/6i+ET (arm A) or CT+/-ET (arm B). Primary endpoint was progression-free survival (PFS). A tumor sample from the primary or metastatic tumor (archived or newly-obtained) was mandatory for inclusion. In this correlative biomarker analysis, tumor-infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLS) were detected on baseline tumor samples by hematoxylin&eosin staining, while immune genomic signatures were assessed with the nCounter BC360 panel. Immune pattern at immunohistochemistry was defined as inflamed (IF), excluded (IE) or desert (ID). TILs and signatures were dichotomized (high vs. low) with the maximally-selected rank statistics (MSRS) method. Survival analyses were conducted with the Kaplan-Meier (KM) method and differences were tested with log-rank test. Hazard ratios (HR) with 95% confidence intervals (CI) were estimated with Cox regression. Significance was set at p≤0.05. Since the trial was stopped earlier due to slow accrual all analyses were exploratory. Results: Forty-nine patients were randomized, 17 (34.7%) in arm A and 32 (65.3%) in arm B. No significant clinicopathological differences were observed at baseline between the two arms, except for tumors in arm B showing more TLS (50.0% vs. 12.5%, p=0.013). Median PFS (mPFS) with CT+/-ET was numerically shorter than mPFS with CDK4/6i+ET (11.2 vs. 19.9 months, HR: 1.41, 95%CI: 0.75-2.64, p=0.289). The median OS (mOS) for arm A was not estimable (NE) vs. 30.6 months in arm B (p=0.283). In arm A, median TILs levels were 3% (interquartile range [IQR]: 1-5%) and TLS, with/without germinal centers, were present in 2 cases (12.5%). These were also the only IF tumors in the arm, whereas the rest (87.5%) were ID. In arm B, 7 (25.0%) tumors were IF, 19 (87.5%) ID and 2 (7.1%) IE. Median TILs were 4.5% (IQR: 2-12.8%) and TLS were present in 50% cases. In arm A, ID tumors showed lower mPFS than IF (15.8 vs. 27.5 months), with concordant trend at the OS KM curve. In arm B there was no clear difference in PFS, but IF tumors did not reach mOS, differently from ID (28.7 months) and IE (28.1 months). High vs. low TILs levels were significantly associated with better PFS (p=0.003) and OS (p=0.005) in arm A. High levels of a TGFβ gene expression signature were significantly associated with better PFS (p=0.020) and OS (p=0.005) in arm A and PFS (p=0.03) in arm B; higher levels of a cytokine/chemokine signature were associatedwith better PFS (p=0.02) in arm A, and higher levels of a mastcells signature was associated with worse OS in both arms (p=0.02 and p=0.03). In arm B, higher levels of a macrophage (p < 0.001) and antigen presentation signatures (p=0.04) were associated with worse and better OS, respectively, whereas higher levels of an immune infiltration and a cytotoxic cells signature were associated with better PFS (p=0.03 both). TLS presence was numerically associated to longer mPFS (23.5 vs. 15.8 months) in arm A, with consistent OS KM curve’s trend, and longer mOS (44.5 vs. 28.1 months) in arm B. Conclusions: The KENDO trial further supports CDK4/6i+ET use in aggressive CT-naïve HR+/HER2- MBC. Biomarkers of immune activation such as IF tumors, higher TILs and presence of TLS pointed towards better survival outcomes. Genomic immunological features also showed prognostic effect, with differences according to treatment arm and/or the immune process or cell line tracked. Further research on larger cohorts is needed to confirm these preliminary findings. Citation Format: Francesco Schettini, Michela Palleschi, Francesca Mannozzi, Fara Brasó-Maristany, Lorenzo Cecconetto, Patricia Galván, Marita Mariotti, Alessia Ferrari, Emanuela Scarpi, Anna Miserocchi, Oriana Nanni, Esther Sanfeliu, Aleix Prat, Andrea Rocca, Ugo De Giorgi. Immunologic features and association with prognosis in hormone receptor-positive/HER2-negative (HR+/HER2-) metastatic breast cancer (MBC) treated with chemotherapy (CT) or CDK4/6-inhibitors (CDK4/6i) + endocrine therapy (ET) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-14-06.

Significance of Pre-Treatment CALLY Score Combined with EBV-DNA Levels for Prognostication in Non-Metastatic Nasopharyngeal Cancer Patients: A Clinical Perspective.

The C-reactive protein-albumin-lymphocyte (CALLY) score is a novel indicator associated with inflammation, immunity, and nutrition, utilized for cancer prognostic stratification. This study aimed to evaluate the integrated prognostic significance of the pre-treatment CALLY score and Epstein-Barr virus (EBV) DNA levels in nasopharyngeal carcinoma (NPC) patients and to develop prognostic models. A total of 1707 NPC patients from September 2015 to December 2017 were retrospectively enrolled. The cut-off point for the CALLY score, determined by maximum selected rank statistics, integrates with the published cut-off point for pre-EBV DNA to develop a comprehensive index. Subsequently, patients were randomly allocated in a 1:1 ratio into training and validation cohorts. Survival analysis was conducted using the Kaplan-Meier method with Log rank tests, and the Cox proportional hazards model was applied to identify independent prognostic factors for constructing predictive nomograms. The predictive ability of the nomograms were assessed through the concordance index (C-index), calibration curves, and decision curve analysis. By integrating CALLY scores and EBV-DNA levels, patients were categorized into three risk clusters. Kaplan-Meier curves reveal significant differences in overall survival (OS), distant metastasis-free survival (DMFS), and locoregional relapse-free survival (LRRFS) outcomes among different risk groups (all P values < 0.05). Multivariate analysis revealed that CALLY-EBV DNA index serves as an independent prognostic factor for the OS, DMFS, and LRRFS. The prognostic nomograms based on the CALLY-EBV DNA index provided accurate predictions for 1-year, 3-year, and 5-year OS, DMFS, and LRRFS. Additionally, compared to the traditional TNM staging system, the nomograms exhibited enhanced discriminatory power, calibration capability, and clinical applicability. All results were in agreement with the validation cohort. The CALLY-EBV DNA index is an independent prognostic biomarker. The nomogram prediction models, constructed based on the CALLY-EBV DNA index, demonstrates superior predictive performance compared to the traditional TNM staging.

Relationship of the Neutrophil-Lymphocyte Ratio with All-Cause and Cardiovascular Mortality in Patients with Diabetic Kidney Disease: A Prospective Cohort Study of NHANES Study.

To investigate the association between the NLR and the risk of all-cause and cardiovascular mortality in US adults with diabetic kidney disease (DKD). The data utilized for this analysis were sourced from ten National Health and Nutrition Examination Survey cycles (1999-2018) with mortality data (up to 31 December 2019) via linkage to the National Death Index. The optimum NLR threshold for predicting survival outcomes was determined through the maximally selected rank statistics. Restricted cubic spline (RCS), weighted Cox proportional hazard regression, stratified analyses, and time-dependent receiver-operating characteristic curve (ROC) were employed to delineate the prospective correlations of the NLR with both all-cause and cardiovascular mortality. In this investigation, a cohort comprising 2581 patients diagnosed with DKD was examined, encompassing 624 individuals with a higher NLR (≥3.07) and 1957 subjects with a lower NLR (<3.07). Over a median follow-up of 79 months (interquartile range, 44-128 months), 1103 deaths occurred, including 397 from cardiovascular causes and 706 from non-cardiovascular causes. The RCS analysis elucidated the positive linear correlation (both nonlinear P > 0.05). In the multivariable analyses, each one-unit increase in the NLR value was correlated with a 51% increased risk of all-cause mortality (1.51(1.28, 1.77)) and a 71% increased risk of cardiovascular mortality (1.71(1.32, 2.21)). The results were largely consistent across stratified analyses encompassing variables such as age, sex, race/ethnicity, marital status, family income, education levels, BMI, drinking status, smoking status, hypertension, CVD, and anti-infective drugs (P for interaction >0.05 for all). Time-dependent ROC analyses underscored the NLR's credible predictive efficacy for both short-term and extended durations in forecasting both all-cause and cardiovascular mortality. The findings emphasize the promising use of the NLR in stratifying and prognosticating the risk of mortality in DKD in clinical practice.

Characteristics of Tonsillitis in Children at Massenrempulu Enrekang Regional Hospital During The Period 2017-2022

Tonsillitis, an inflammation of the tonsils due to viral or bacterial infection, manifests with symptoms such as sore throat, tonsil swelling, difficulty swallowing, and fever. While the World Health Organization (WHO) lacks specific global tonsillitis incidence data, Indonesian Ministry of Health's 2018 statistics rank tonsillitis as the 10th most common ailment among 5-9-year-olds. Objective to characterize tonsillitis among children at Massenrempulu Enrekang Regional General Hospital during 2017-2022. The method used is descriptive research with a univariate design. The total sample size is 93, using total sampling technique, and analyzed with a univariate design. The results obtained showed that the age characteristics were as follows: children aged 6-11 years constitute 41 patients (44.1%), early adolescents aged 12-16 years constitute 31 patients (33.3%), toddlers aged 0-5 years constitute 14 patients (15.1%), and late adolescents aged 17-18 years constitute 7 patients (7.5%). The distribution of gender indicates that female patients are 52 (55.9%), while male patients are 41 (44.1%). Parental education level shows that moderate education level is represented by 52 patients (55.9%), followed by high education level by 37 patients (39.8%), and low education level by 4 patients (4.3%). A history of upper respiratory tract infections was found in 85 patients (91.4%), while only 8 patients (8.6%) had no history of upper respiratory tract infections. Allergy history was present in 68 patients (73.1%), while 25 patients (26.9%) had no history of allergies.

Optimal cut-off value for identifying objective response in patients with nasopharyngeal carcinoma after induction chemotherapy.

We aimed to establish the most suitable threshold for objective response (OR) in the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 in patients with nasopharyngeal carcinoma (NPC). According to RECIST 1.1, we retrospectively evaluated MR images of NPC lesions in patients before and after induction chemotherapy (IC). Restricted cubic spline and maximally selected rank statistics were used to determine the cut-off value. Survival rates and differences between groups were compared with Kaplan-Meier curves and log-rank tests. Of 1126 patients, 365 cases who received IC treatment were suitable for RECIST 1.1 evaluation. The 20% cut-off value maximized between-group differences according to maximally selected rank statistics. No difference in distant metastasis-free survival between OR and non-response groups was shown using the primary threshold of OR (30%), while it differed when 20% was employed. With an optimal cut-off value of 20%, RECIST may assist clinicians to accurately evaluate disease response in NPC patients.

Abstract 7668: Novel pretreatment nomograms based on pan-Immune-inflammation value for predicting clinical outcome in patients with head and neck squamous cell carcinoma

Abstract Background: The prognostic value of an effective biomarker, Pan-Immune-Inflammation Value (PIV), for head and neck squamous cell carcinoma (HNSCC) patients after radical surgery or chemoradiotherapy has not been well explored. This study aimed to construct and validate nomograms based on PIV to predict survival outcomes of HNSCC patients. Methods: 161 HNSCC patients underwent radical surgery and 50 patients received chemoradiotherapy were enrolled retrospectively for development and external validation cohort, respectively. The cut-off of PIV was determined using the maximally selected rank statistics method. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to develop two nomograms (Model A and Model B) that predict disease-free survival (DFS). Results: Patients with higher PIV (≥123.3) experienced a worse DFS (HR: 5.01, 95% CI: 3.25-7.72, p&amp;lt;0.0001) and overall survival (OS) (HR: 5.23, 95% CI: 3.34-8.18, p&amp;lt;0.0001) compared to patients with lower PIV (&amp;lt;123.3), which was also consistent in the external cohort. Predictors of Model A included age, TNM stage, neutrophil-to-lymphocyte ratio (NLR) and PIV, and that of Model B included TNM stage, lymphocyte-to-monocyte ratio (LMR) and PIV. In comparison with TNM stage alone, the concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves of the nomograms demonstrated good calibration and discrimination, and the decision curve analysis (DCA) also showed satisfactory clinical utility in both internal and external validation. Conclusions: The nomograms based on PIV, a simple but forceful indicator, can provide intuitive and precise prognosis prediction of individual HNSCC patients after radical surgery or chemoradiotherapy. Citation Format: Qian Chen, Xiang Li, Yanxia Bai, Yue Chen. Novel pretreatment nomograms based on pan-Immune-inflammation value for predicting clinical outcome in patients with head and neck squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7668.

Abstract 6426: Identification of potential immune biomarkers for GSK-3 inhibitor elraglusib (9-ING-41) in patients with relapsed/refractory metastatic cancer

Abstract Cytokines mediate strong immunomodulatory effects in cancer. Elraglusib (9-ING-41), an inhibitor of GSK-3, is a potent antitumor and immune-modulatory agent in phase 2 clinical trials for the treatment of various cancers. Here, we examined the immune environment of elraglusib-treated cancer patients by measuring peripheral blood protein levels to explore whether the expression level of cytokines/chemokines/soluble cell receptors/growth factors (CCSG) is correlated with clinical outcome. Using a customized Luminex platform, the expression of forty CCSG hypothesized to be linked to GSK-3 activity was assessed in pre-dose plasma samples obtained from 45 cancer patients with relapsed/refractory metastatic disease (NCT03678883; the 1801 trial). All patients in the 1801 trial were treated with elraglusib (dose range: 1-15 mg/kg) either as a single agent (Part 1; n=21) or in combination with chemotherapy (Part 2; n=24). Pre-dose peripheral blood protein levels were examined as binary predictors of clinical outcome using optimal cutoff points determined by maximally selected rank statistics. In the aggregate Part 1 and 2 populations (n=45), we identified 13 CCSG that significantly stratified the cohort by overall survival (OS). High pre-dose levels of CD95 and TNFRSF10C were associated with better OS. CD95 was a better prognostic of OS than TNFRSF10C (HR: 2.27, 95% CI: 1.10-4.67, p-value: 0.023). Low pre-dose levels of 11 CCSG were also significantly associated with favorable OS, with IL-8 being the most predictive (HR: 0.137, 95% CI: 0.0545-0.346, p-value: &amp;lt;0.0001). Part 1 and 2 predose samples were also analyzed separately, and many of the biomarkers identified in the aggregate analysis retained significance in the separated analysis. In Part 1, CXCL5, IFN-alpha, and IL-18 emerged as unique markers, and in Part 2, CCL22 was the single unique marker.The results of our exploratory study identified several putative biomarkers of elraglusib clinical benefit and demonstrated potential immunomodulatory mechanisms of elraglusib that will be used to inform the further clinical development of elraglusib for the treatment of metastatic cancer. Citation Format: Taylor Weiskittel, Kelsey Huntington, Leiqing Zhang, Austin Koukol, Benedito A. Carneiro, Hu Li, Andrey Ugolkov, Wafik El-Deiry, Andrew Mazar. Identification of potential immune biomarkers for GSK-3 inhibitor elraglusib (9-ING-41) in patients with relapsed/refractory metastatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6426.

Abstract 4852: High brain relapse rates in stage III triple negative inflammatory breast cancer are independent of systemic therapy

Abstract Background - Inflammatory breast cancer (IBC) is an aggressive subtype of invasive breast carcinoma that confers a comparatively poorer prognosis owing to consistently observed inferior responses to systemic therapies as compared to non-IBC cases. Triple negative (TN) breast cancer which is characterized by lack of estrogen receptor (ER) and progesterone receptor (PR) expression, as well as by lack of HER2 amplification portends particularly poor outcomes including high rates of brain failure. Here we reviewed our prospective IBC registry data for contemporary TNIBC patients to assess current outcomes and brain failure risk in the context of standard neoadjuvant immunotherapy. Methods - Given the change to the inclusion of pembrolizumab in addition to chemotherapy in the neoadjuvant setting in 2020, we reviewed records from 2016-2023 for Stage III TNIBC patients who presented to MD Anderson Cancer Center (MDACC) prior to receiving other therapy. TNIBC was defined as ER &amp;lt;1%, PR &amp;lt;1%, HER2 IHC 0/1+ or ISH-. N = 38. We examined PCR and brain mets as first failure by regimen (KN522, ACT, AC/TC) and compared using descriptive statistics. Log rank statistic was used to compare overall survival (OS) by PCR. Patients with stage III TNIBC who started the KN522 regimen achieved a pCR rate of 35% (N= 20) and pCR was less frequent in postmenopausal KN522 patients (1/7 PCRs. P = 0.016). Among this cohort, 20% of patients experienced relapse in the CNS as a site of first failure including two patients who achieved a PCR, and 25% had any brain failure at a median follow up post-surgery of 8M. Among 9 patients treated with AC/T 22% achieved pCR with 22% brain metastasis relapse rate as site of first failure and 33% overall was observed at a median follow up of 14M post-surgery. In 9 patients receiving AC/TC, the PCR was 44% and any brain relapse rate was 22%, 1/2 was a site of first failure, median follow up 38M. Despite similarities in brain relapse rates, achieving pCR nonetheless correlated with improved overall survival, P &amp;lt; 0.05. For comparison, among 11 stage IV TNIBC patients treated with neoadjuvant systemic therapy pre-KN522, median follow up 22M from initial diagnosis, 6/11 patients developed brain involvement, 5/6 as a site of first failure. Given small numbers it is difficult to compare PCR by regimen, however we note the PCR in KN522 is lower than expected, and the rate of brain metastases particularly as a site of first failure is consistently high across regimens regardless of PCR. It is critical to consider brain penetrance of neoadjuvant systemic therapies, brain staging and even prophylaxis of brain metastasis in patients with non-metastatic and metastatic TNIBC. Current efforts are ongoing to determine molecular signatures which may aid in prognostication and potentially study design to incorporate prophylactic therapies with the overarching goal of improving outcomes in patients with triple negative IBC. Citation Format: Azadeh Nasrazadani, Megumi Kai, Rachel Layman, Vicente Valero, Sadia Saleem, Bisrat G. Debeb, Anthony Lucci, Susie X. Sun, Swetha Bopparaju, Hope E. Murphy, Angela Alexander, Angela N. Marx, Michael C. Stauder, Bora Lim, Wendy A. Woodward. High brain relapse rates in stage III triple negative inflammatory breast cancer are independent of systemic therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4852.

Imaging-guided prognostic score-based approach to assess the benefits of combotherapy versus monotherapy with immune checkpoint inhibitors in metastatic MSI-H colorectal cancer patients

BackgroundThis retrospective study determined survival responses to immune checkpoint inhibitors (ICIs), comparing mono- (mono) and combo-immunotherapy (combo) in patients with microsatellite instability-high (MSI-H) metastatic colorectal cancer (mCRC) by analyzing quantitative imaging data and clinical factors. MethodsOne hundred fifty patients were included from two centers and divided into training (n = 105) and validation (n = 45) cohorts. Radiologists manually annotated chest-abdomen-pelvis computed tomography and calculated tumor burden. Progression-free survival (PFS) was assessed, and variables were selected through Recursive Feature Elimination. Cutoff values were determined using maximally selected rank statistics to binarize features, forming a risk score with hazard ratio-derived weights. ResultsIn total, 2258 lesions were annotated with excellent reproducibility. Key variables in the training cohort included: total tumor volume (cutoff: 73 cm3), lesion count (cutoff: 20), age (cutoff: 60) and the presence of peritoneal carcinomatosis. Their respective weights were 1.13, 0.96, 0.91, and 0.38, resulting in a risk score cutoff of 1.36. Low-score patients showed similar overall survival and PFS regardless of treatment, while those with a high-score had significantly worse survivals with mono vs combo (P = 0.004 and P = 0.0001). In the validation set, low-score patients exhibited no significant difference in overall survival and PFS with mono or combo. However, patients with a high-score had worse PFS with mono (P = 0.046). ConclusionsA score based on total tumor volume, lesion count, the presence of peritoneal carcinomatosis, and age can guide MSI-H mCRC treatment decisions, allowing oncologists to identify suitable candidates for mono and combo ICI therapies.

Data-driven learning-based classification model for mitigating false data injection attacks on dynamic line rating systems

The increasing need to explore electric power grid expansion technologies like dynamic line rating (DLR) systems and their dependence on real-time weather data for system planning necessitates research into false data injection attacks (FDIA) on cyber-physical power systems (CPS). This study aims to develop a robust machine learning model to mitigate FDIA in DLR systems, focusing on statistical data processing, feature ranking, selection, training, validation and evaluation. It synthesises z-score and other statistical analyses with minimum redundancy maximum relevance (MR-MR) feature ranking and selection algorithm to improve model performance and generalisation of binary generalised linear model logistic regression (BGLM-LR) and other machine learning classification algorithms. The resulting models formed with BGLM-LR, Gaussian naïve Bayes (GNB), linear support vector machine (LSVM), wide neural network (WNN), and decision tree (DT) were trained and tested with 10-year hourly DLR history data features. The evaluation of the models on unseen data revealed enhanced validation and testing accuracies after the MR-MR feature ranking and selection. BGLM-LR, GNB, LSVM, and WNN showed promising performance for mitigating FDIA. However, the study identifies DT’s limitations as overfitting and lacking generalisation in FDIA mitigation. z-score-MR-MR-BGLM-LR and z-score-MR-MR-LSVM models exhibited outstanding performances with zero false negative rates highlighting the significance of feature ranking and selection. Still, the z-score-MR-MR-BGLM-LR combination exhibits the highest marginal improvement from training to testing, the lowest training and validation time and a perfect area under curve (AUC) of the receiver operating characteristics making it the best choice in mitigating FDIA when computational resources are limited.

Prognostic value of cerebrospinal fluid tumor cell count in leptomeningeal disease from solid tumors.

Treatment decisions for leptomeningeal disease (LMD) rely on patient risk stratification, since clinicians lack objective prognostic tools. The introduction of rare cell capture technology for identification of cerebrospinal fluid tumor cells (CSF-TCs), such as CNSide assay, improved the sensitivity of LMD diagnosis, but prognostic value is unknown. This study assesses the prognostic value of CSF-TC density in patients with LMD from solid tumors. We conducted a retrospective cohort study of patients with newly diagnosed or previously treated LMD from a single institution who had CNSide assay testing for CSF-TCs from 2020 to 2023. Univariable and multivariable survival analyses were conducted with Cox proportional-hazards modeling. Maximally-selected rank statistics were used to determine an optimal cutpoint for CSF-TC density and survival. Of 31 patients, 29 had CSF-TCs detected on CNSide. Median (interquartile range [IQR]) CSF-TC density was 67.8 (4.7-639) TCs/mL. CSF cytology was positive in 16 of 29 patients with positive CNSide (CNSide diagnostic sensitivity = 93.5%, negative predictive value = 85.7%). Median (IQR) survival from time of CSF-TC detection was 176 (89-481) days. On univariable and multivariable analysis, CSF-TC density was significantly associated with survival. An optimal cutpoint for dichotomizing survival by CSF-TC density was 19.34 TCs/mL. The time-dependent sensitivity and specificity for survival using this stratification were 76% and 67% at 6 months and 65% and 67% at 1 year, respectively. CSF-TC density may carry prognostic value in patients with LMD from solid tumors. Integrating CSF-TC density into LMD patient risk-stratification may help guide treatment decisions.

Longer time to testosterone recovery impacts favorably on outcomes for prostate cancer following androgen deprivation and radiotherapy.

To evaluate the impact of sustained hypogonadism after androgen deprivation therapy (ADT) associated with radiotherapy in prostate cancer (PCa) patients with biochemical relapse-free survival (bRFS). Aretrospective cohort analysis of 213consecutive PCa patients referred for radiotherapy plus ADT was carried out. Follow-up times including time to testosterone recovery (TTR) and bRFS were calculated from the end of ADT. Univariate and multivariate Cox regression analyses predicting bRFS were used. The optimal cutoffs for TTR and duration of ADT were determined using the maximally selected rank statistics (MSRS). After amedian follow-up of 104 months, 18patients relapsed among those who had recovered testosterone levels and 9 among those who did not. Median ADT duration was 36months. The optimal cutoff for TTR was determined using MSRS. TTR >48months was significantly associated with better bRFS (logrank, p < 0.0027). Five-year bRFS was 100% for >48months vs. 85% for <48months. TTR was the only significant variable for bRFS in multivariate Cox analysis. Our data show an association between longer TTR and bRFS values among PCa patients treated with ADT.

Predictive role of intracranial PD-L1 expression in a real-world cohort of NSCLC patients treated with immune checkpoint inhibition following brain metastasis resection

BackgroundEmerging evidence suggests that treatment of NSCLC brain metastases with immune checkpoint inhibitors (ICIs) is associated with response rates similar to those of extracranial disease. Programmed death-ligand 1 (PD-L1) tumor proportion score (TPS) serves as a predictive biomarker for ICI response. However, the predictive value of brain metastasis-specific (intracranial) PD-L1 TPS is not established. We investigated the role of intra- and extracranial PD-L1 TPS in NSCLC patients treated with ICI following brain metastasis resection.MethodsClinical data from NSCLC patients treated with ICI following brain metastasis resection (n = 64) were analyzed. PD-L1 TPS of brain metastases (n = 64) and available matched extracranial tumor tissue (n = 44) were assessed via immunohistochemistry. Statistical analyses included cut point estimation via maximally selected rank statistics, Kaplan–Meier estimates, and multivariable Cox regression analysis for intracranial progression-free survival (icPFS), extracranial progression-free survival (ecPFS), and overall survival (OS).ResultsPD-L1 expression was found in 54.7% of brain metastases and 68.2% of extracranial tumor tissues, with a median intra- and extracranial PD-L1 TPS of 7.5% (0 – 50%, IQR) and 15.0% (0 – 80%, IQR), respectively. In matched tissue samples, extracranial PD-L1 TPS was significantly higher than intracranial PD-L1 TPS (p = 0.013). Optimal cut points for intracranial and extracranial PD-L1 TPS varied according to outcome parameter assessed. Notably, patients with a high intracranial PD-L1 TPS (> 40%) exhibited significantly longer icPFS as compared to patients with a low intracranial PD-L1 TPS (≤ 40%). The cut point of 40% for intracranial PD-L1 TPS was independently associated with OS, icPFS and ecPFS in multivariable analyses.ConclusionOur study highlights the potential role of intracranial PD-L1 TPS in NSCLC, which could be used to predict ICI response in cases where extracranial tissue is not available for PD-L1 assessment as well as to specifically predict intracranial response.

Lymph node yield: Impact on oncologic outcomes in oral cavity cancer.

Lymph node metastases are associated with poor prognosis in oral cavity squamous cell carcinoma (OCSCC). In other cancers, clinical guidelines on the number of lymph nodes removed during primary surgery, lymph node yield (LNY), exist. Here, we evaluated the prognostic capacity of LNY on regional failure, locoregional recurrence, and disease-free survival (DFS) in patients with OCSCC treated by primary neck surgery. This retrospective cohort study took place at Sunnybrook Health Sciences Centre in Toronto, Canada and involved a chart review of all adult patients with treatment-naive OCSCC undergoing primary neck dissection. For each outcome, we first used the maximally selected rank statistics and an optimism-corrected concordance to identify an optimal threshold of LNY. We then used a multivariable Cox proportional hazards model to assess the association between high LNY (>threshold) and each outcome. Among the 579 patients with OCSCC receiving primary neck dissection, 61.7% (n = 357) were male with a mean age of 62.9 years (standard deviation: 13.1) at cancer diagnosis. When adjusting for sociodemographic and clinical factors, LNY >15 was significantly associated with improved DFS (adjusted HR [aHR]: 0.73, 95% CI: 0.54-0.98), locoregional recurrence (aHR: 0.68, 95% CI: 0.49-0.95), and regional failure (aHR: 0.61, 95% CI: 0.39-0.93). Our study findings suggested high LNY to be a strong independent predictor of various patient-level quality of surgical care metrics. The optimal LNY we found (15) was lower than the conventionally recommended (18), which calls for further research to establish validity in practice.