Predictor Of Overall Survival Research Articles

Correlation between number of molecular mutations and outcomes in de novo acute myeloid leukemia.

e18513 Background: Genomic sequencing of cancer has led to a deeper genetic understanding of the pathogenesis of acute myeloid leukemia (AML). Studies in myelodysplastic syndrome have shown that as the number of oncogenic mutations increases, patient outcomes progressively worsen. We hypothesized that patients with AML may also have a worse prognosis if they have a higher number of somatic mutations. To test this hypothesis, we examined the somatic mutational profile of 225 patients with previously untreated AML. Methods: A single-center retrospective analysis was done utilizing the cancer registry and evaluated patients with de novo AML diagnosed between January 2015 to January 2021. Patient characteristics, cytogenetics, and molecular data were collected by chart review. Patients with available cytogenetic and somatic mutations profile from next-generation sequencing (NGS) were included. Clinically significant (CS) mutations for AML were detected by NGS performed on the diagnostic bone marrow specimen. Statistical analysis was done using the Mann-Whitney U test for continuous variables and proportions were compared using Chi-square test. Results: A total of 225 De Novo AML patients met inclusion criteria. The median age at diagnosis was 61 (range, 21-86). The population was fairly distributed among males (52%) and females (48%). Approximately 51% (n=115) of patients had 0-2 mutations, 43% (n=97) had 3-5 mutations, and 6 % (n=13) had >5 CS mutations. The median number of CS mutations for the entire cohort was 2 (range: 0-9). Survival was worse in the group with >5 mutations when compared to those with 5 or less mutations (23 vs 7 months, p= 0.012). Patients with intermediate risk cytogenetics had a higher median number of CS mutations compared to the favorable and adverse risk group combined (3 versus 1, p < 0.001). To determine whether overall survival was impacted by the presence of an adverse mutation, a subgroup analysis was done using 43 patients with a normal karyotype and at least 1 adverse mutation. The cohort with >5 CS mutations had a significantly shorter OS compared to patients with ≤5 CS mutations (43 vs 9 months, p= 0.001). Conclusions: We found that patients with intermediate-risk cytogenetics have a high number of CS mutations. We found that a higher number of mutations (>5) led to statistically significant difference in survival. To determine whether this difference in survival was a result of the presence of adverse risk mutations vs. number of mutations alone, we analyzed our patients who had normal karyotype with at least one adverse genetic mutation and stratified them based on number of mutations. The presence of more than 5 CS mutations was associated with a worse OS. The number of clinically significant mutations may be an independent predictor of overall survival in AML. This can serve as another tool in stratifying AML risk with normal karyotype. A large prospective clinical trial is necessary to validate.

Survival outcome and predictors of WHO grade 2 and 3 insular gliomas: A classification based on the tumor spread

AbstractObjectiveThe study aimed to identify if clinical features and survival outcomes of insular glioma patients are associated with our classification based on the tumor spread.MethodsOur study included 283 consecutive patients diagnosed with histological grade 2 and 3 insular gliomas. A new classification was proposed, and tumors restricted to the paralimbic system were defined as type 1. When tumors invaded the limbic system (referred to as the hippocampus and its surrounding structures in this study) simultaneously, they were defined as type 2. Tumors with additional internal capsule involvement were defined as type 3.ResultsTumors defined as type 3 had a higher age at diagnosis (p = 0.002) and a higher preoperative volume (p < 0.001). Furthermore, type 3 was more likely to be diagnosed as IDH wild type (p < 0.001), with a higher rate of Ki‐67 index (p = 0.015) and a lower rate of gross total resection (p < 0.001). Type 1 had a slower tumor growth rate than type 2 (mean 3.3%/month vs. 19.8%/month; p < 0.001). Multivariate Cox regression analysis revealed the extent of resection (HR 0.259, p = 0.004), IDH status (HR 3.694, p = 0.012), and tumor spread type (HR = 1.874, p = 0.012) as independent predictors of overall survival (OS). Tumor grade (HR 2.609, p = 0.008), the extent of resection (HR 0.488, p = 0.038), IDH status (HR 2.225, p = 0.025), and tumor spread type (HR 1.531, p = 0.038) were significant in predicting progression‐free survival (PFS).ConclusionThe current study proposes a classification of the insular glioma according to the tumor spread. It indicates that the tumors defined as type 1 have a relatively better nature and biological characteristics, and those defined as type 3 can be more aggressive and refractory. Besides its predictive value for prognosis, the classification has potential value in formulating surgical strategies for patients with insular gliomas.

Immunological profiling of glioblastoma cellular composition to predict response to dendritic cell vaccination.

e14037 Background: Glioblastomas are the most common primary malignant brain tumors, comprising 2% of all adult cancers. Despite recent advancements in genetic classification and targeted therapies for specific mutations, there has been no significant improvement in overall life expectancy for the majority of patients. Last year, our research group reported promising results from a phase II prospective trial involving allogeneic dendritic cell vaccination. To date, six out of 37 reported cases remain alive without tumor recurrence, exhibiting a performance status of 90 to 100% according to the Karnofsky Performance Scale (KPS) three years after the initiation of vaccination. Methods: In this study, we focused on the immune cell infiltration observed at the time of tumor excision in enrolled patients. We utilized flow cytometry to quantify cells expressing membrane CD86, CD45, HLA-DR, PD-L1, CD11b, and CD14, in addition to assessing IDH-1 status, age, gender, KPS, gender, ECOG, symptomatology, and the number of vaccines administered during the trial. Our goal was to predict responsiveness in terms of overall survival using a neural network prediction algorithm with three hidden nodes and five seeds for improved reproducibility. We employed the random holdback method for algorithm validation. Results: From the 37 enrolled patients, we successfully obtained viable tumor cells from 19 frozen samples. The model achieved an RSquare value of 0.71 after training and 0.66 after validation (where 1 indicates a perfect model and 0 implies no improvement over a constant model). Similar RSquare values in both training and validation sets indicate strong predictive power. Positive predictors of overall survival included HLA-DR positivity, PD-L1 positivity, IDH-1 mutation status, the presence of focal deficits, and higher KPS scores, while negative predictors were CD86 expression, older age, symptoms of intracranial hypertension (ICH), and higher ECOG performance status. Conclusions: In conclusion, the neural network algorithm described herein enables the prediction of responsiveness to dendritic cell vaccination in terms of overall survival, based on clinical features and the profile of immune cell infiltration observed at the time of tumor excision.

Origin associated with heterogeneity amongst Hispanic patients with breast cancer in the United States.

e23077 Background: There are over 50 million self-identifying Hispanics in the United States. This, however, represents a heterogenous population variably affected by an array of determinants of health, including race and insurance status. We used a national registry to investigate for significant differences in outcomes of Hispanic patients with breast cancer in the United States by country of origin. Methods: We identified a cohort of Hispanic patients in the United States with breast cancer for which origin was documented using the 2004-2019 National Cancer Database (NCDB) dataset. The NCDB delineates the following specific origins: Puerto Rico, Mexico, Cuba, South or Central America (excluding Brazil), or the Dominican Republic. We performed multivariate logistic regression modeling to identify whether origin was a significant predictor of advanced cancer staging at diagnosis (AJCC stage III or IV), adjusting for age, race, receptor subtype, histology, grade, insurance status, and facility type. Consequently, we used Cox Regression survival modeling to investigate whether overall survival (OS) differed by Hispanic origin after adjusting for stage at diagnosis and other confounders of survival: age, race, stage at diagnosis, receptor subtype, and systemic therapy received. Results: Of the identified n = 60,438 Hispanic patients with breast cancer in the United States: n = 26,800 (44.3%) had Mexican, n = 9,792 (16.2%) had Puerto Rican, n = 5,283 (8.8%) had Cuban, n = 14,381 (23.8%) had South/Central American, and n = 4,172 (6.9%) had Dominican Republic origins. After adjusting for the aforementioned covariates, we found that origin was a significant predictor of staging at diagnosis (p < 0.001). Patients originally from Mexico were more likely to be diagnosed at advanced stages compared to patients from Puerto Rico (OR 1.31; 95% CI, 1.18-1.46; p < 0.001). We also identified that origin was a significant predictor of overall survival in this cohort even when controlling for various confounders, including stage at diagnosis. Compared to patients from Puerto Rico, patients from Central/South America (HR 0.78, 95% CI 0.70-0.88, p < 0.001) and patients from the Dominican Republic (HR 0.77, 95% CI 0.65-0.92, p = 0.003) exhibited significantly improved overall survival. There was no statistically-significant survival difference between patients from Mexico and patients from Puerto Rico. Conclusions: This real-world analysis showed that, for Hispanic individuals living in the US with breast cancer, origin is significantly associated with outcomes even after accounting for other known determinants of health. We suggest that region of origin should be studied further as a potential determinant of outcomes in patients with cancer.

Overall survival prediction and risk stratification in patients with neuroblastoma through machine learning in the large multi-institutional PRIMAGE cohort.

10054 Background: Neuroblastoma (NB) is the most prevalent solid cancer in childhood in which imaging plays a pivotal role at every step of the patient's journey. This investigation aimed to develop a machine learning model using clinical, molecular (MycN amplification), and magnetic resonance (MR) radiomics features at diagnosis to predict patient’s overall survival (OS) and improve their risk stratification. Methods: A database comprising clinical, molecular, and International Neuroblastoma Risk Group (INRG) staging on 513 patients with accessible MR imaging (discovery cohort) was employed for model training, validation, and testing. An additional 22 patients from non-discovery cohort hospitals served as an external validation group. Tumor segmentations of NB were manually and semi-automatically performed on corresponding T2-weighted MR images by an experienced radiologist. In total, 107 radiomics features were extracted and harmonized across MR scan manufacturers and magnetic field strengths using the nested ComBat methodology to correct both batch effects. These radiomics features, combined with clinical and molecular data, were utilized as input for the models. A nested cross-validation approach was employed for model development to determine the optimal preprocessing, machine learning algorithm, and model configuration. Results: The discovery cohort yielded a C-index of 0.788 ± 0.049 in the test partitions, with a random survival forest (RSF) exhibiting the best performance. In the validation cohort, a C-index of 0.934 was achieved. Interpretability analysis identified lesion heterogeneity, size, and molecular variables as crucial factors in OS prediction. The model demonstrated superior predictive performance and patient stratification compared to conventional staging systems in both cohorts. Conclusions: The RSF predictive model exhibited high performance, emphasizing the significant contribution of radiomics features and alignment with established clinical and molecular variables. The model stratified NB patients into low-, intermediate-, and high-risk categories and suggests that radiomics features potentially could improve current risk stratification systems. Additional external validation is warranted as this may present new evidence for enhancing patient care and clinical decision-making for NB patients.

Survival outcomes with adjuvant immunotherapy after hepatic resection in patients with intermediate/advanced (BCLC stage B/C) hepatocellular carcinoma: Insights from a propensity-matched multicenter study.

4096 Background: With the growing interest in adjuvant immunotherapy for reducing recurrence and improving prognosis after hepatic resection in hepatocellular carcinoma (HCC), particularly in high-risk patients, this study aims to evaluate the impact of adjuvant immunotherapy on long-term recurrence and survival in patients with intermediate/advanced HCC. Methods: A prospective multicenter database was utilized to identify patients who underwent curative-intent resection for Barcelona Clinic Liver Cancer (BCLC) stage B/C HCC. Propensity score matching (PSM) was employed to equate recurrence-free survival (RFS) and overall survival (OS) between patients receiving adjuvant immune checkpoint inhibitors (ICIs) and those who did not. Multivariate Cox-regression analysis was used to identify independent predictors of RFS and OS. Results: Out of 627 patients, 109 (23.3%) received adjuvant immunotherapy, with most ICI-related adverse reactions being grade I-II. The ICI agents used among these 109 patients were tislelizumab (51.4%, n=56), sintilimab (29.3%, n=32), camrelizumab (9.2%, n=10), pembrolizumab (6.4%, n=7), and toripalimab (3.7%, n=4). All patients receiving adjuvant immunotherapy completed at least 3 months of ICI treatment, with no patients discontinuing the treatment due to irAEs. PSM resulted in 99 matched pairs with comparable baseline characteristics. In this cohort, patients receiving adjuvant immunotherapy showed significantly improved median RFS (29.6 vs. 19.3 months, P=0.031) and OS (35.1 vs. 27.8 months, P=0.036) compared to those who did not. Multivariable analyses confirmed adjuvant immunotherapy as an independent factor for better RFS (HR: 0.630; 95% CI: 0.435-0.914; P=0.015) and OS (HR: 0.601; 95% CI: 0.401-0.898; P=0.013). Subgroup analyses suggested prognostic benefits of adjuvant immunotherapy in both intermediate and advanced-stage HCC. Conclusions: This real-world observational study indicates that adjuvant immunotherapy is associated with improved RFS and OS in patients undergoing curative-intent resection for intermediate/advanced HCC. These findings support the need for future randomized controlled trials to establish definitive evidence for this high-risk population.

Survival outcomes of patients with extensive-stage small cell lung cancer who received treatment with atezolizumab in combination with carboplatin and etoposide: A propensity score adjusted cohort study.

8096 Background: Small cell lung cancer (SCLC) is an aggressive type of lung cancer. Most patients (pts) are diagnosed with extensive-stage disease (ES-SCLC). The cornerstone treatment of ES-SCLC has been platinum-based chemotherapy and etoposide. Combining atezolizumab with carboplatin plus etoposide (Carbo-E) improved overall survival (OS) in ES-SCLC pts and became a new standard for first-line treatment. However, there is a paucity of real-world outcomes in ES-SCLC. Herein, we present the largest and longest follow-up retrospective study analyzing atezolizumab in combination with chemotherapy for treatment of ES-SCLC. Methods: We conducted a retrospective study and included all adult pts (≥ 18 years) with ES-SCLC treated at Cleveland Clinic between 1/2010-12/2022. ES-SCLC was defined as stage IIIB or stage IV. We collected treatment regimens and baseline characteristics including age, sex, race, smoking, alcohol intake history, and comorbidities. Responses were assessed using RECIST response criteria. Both OS and progression-free survival (PFS) were calculated from treatment initiation. We used propensity score (PS) weighting and multivariable Cox proportional hazards ratio (CPH) to adjust for baseline confounding. Results: We identified 561 ES-SCLC pts who received treatment, 375 (67%) received Carbo-E and 160 (29%) received Carbo-E + Atezolizumab (Carbo-E-Atezo). The table describes the baseline characteristics of Carbo-E and Carbo-E-Atezo groups. The median follow-up was 30 months (mo) (IQR: 14 - 59). In the Carbo-E arm, 45 patients (12%) received second-line immune therapy (nivolumab +/- ipilimumab or pembrolizumab). On PS-adjusted logistic regression, pts who received Carbo-E-Atezo had a 1.1 odds ratio (95%CI: 0.85-1.43, P>0.05) to respond compared to pts who received Carbo-E. There was no difference in PS-adjusted median OS between pts who received Carbo-E-Atezo (9.2 mo (95%CI: 8.1-11)) vs. Carbo-E (8.4 mo (95%CI: 7.7-9.0)) (log-rank P>0.05). Similarly, there was no difference in adjusted median PFS between pts who received Carbo-E-Atezo (5.9 mo (95%CI: 5.3-6.9)) vs. Carbo-E (5.5 mo (95%CI: 4.7-5.9)) (P>0.05). Using CPH model, the addition of atezolizumab to Carbo-E did not decrease mortality (Hazard Ratio: 0.84, 95%CI: 0.68-1.04, P>0.05). Male gender and increasing age were predictors of worse OS (P<0.05). Conclusions: Among pts with ES-SCLC, the addition of atezolizumab to the standard chemotherapy regimen of Carbo-E showed no significant difference in PFS or OS in our real-world study. [Table: see text]

Impact of radiation dose to the immune cells in stage IV non-small cell lung cancer in the era of immunotherapy.

e20608 Background: Thoracic radiotherapy now is widely accepted in advanced lung cancer. It is not only been used as palliative therapy but also been involved in Systemic treatments in advanced lung cancer, especially in immune era. However, radiotherapy impairs immune system which can be evaluated by estimated dose of radiation to immune cells (EDRIC). Here, we sought to examine the prognostic impact of the EDRIC in advanced NSCLC in the context of immunotherapy, and to identify the factors influencing EDRIC in this population. Methods: We retrospectively enrolled patients with stage IV NSCLC who had received first-line immunotherapy and thoracic radiation therapy. EDRIC is a specific formulation using a model developed by Jin et al and improved by Ladbury et al, calculated using radiation fraction, mean lung dose (MLD), mean heart dose (MHD), and mean body dose (MBD). Spearman’s rank correlation was used to assess the correlation between variables.Associations between EDRIC [analyzed continuously and categorically (<5.7Gy vs ≥5.7Gy)] and overall survival (OS) and progression-free survival (PFS) were evaluated by Kaplan-Meier and Cox proportional methods. Results: We conducted a retrospectively analysis of 152 patients with stage IV NSCLC patients. GTV (r = 0.2023, p = 0.0137), PTV (r = 0.4139, p < 0.0001) and N (r = 0.1897, p = 0.0193) stage showed a positive correlation with EDRIC. Negative correlations of lymphocyte nadir with EDRIC (r = -0.3172, p < 0.0001), during/pre lymphocyte nadir with EDRIC (r = -0.2102, p = 0.0093), during/post lymphocyte nadir with EDRIC (r = -0.2750, p = 0.0006) were found. Median PFS was shorter among the EDRIC ≥5.7Gy group (10.2months vs 18.6months; p < 0.0001). Median OS was also shorter among the EDRIC ≥5.7Gy group (19.8 months vs 30.2months; p = 0.024). For ORR (38% vs 46%; p = 0.413) and DCR (84% vs 92%; p = 0.304), there was no statistical significance between EDRIC≥5.7Gy and EDRIC < 5.7Gy. Analyzed as a continuous variable, EDRIC was the only factor associated with worse PFS (HR = 1.001, p = 0.018) and OS (HR = 1.002, p = 0.001) in multivariate analysis. Conclusions: In the era of immunotherapy, EDRIC is an independent predictor for PFS and OS in advanced NSCLC, warranting investigation into techniques to optimize radiation dose to the immune compartment.

A preliminary study on the timing of radiotherapy for chemoimmunotherapy in oligometastatic non-small-cell lung cancer with negative driver genes.

e20084 Background: Local radiotherapy (LRT) is reported to provide durable local and distant disease control for oligometastatic non-small cell lung cancer (NSCLC) in accumulating evidence, but research on the optimal initial time point remains scarce. We conducted a study to preliminarily evaluate the timing of radiotherapy for chemoimmunotherapy in Oligometastatic Non-small-cell lung cancer with negative driver genes. Methods: 50 patients diagnosed with Oligometastatic Non-small-cell lung cancer with negative driver genes who were treated with chemoimmunotherapy and radiotherapy were retrospectively recruited between January 2018 and October 2023. They were divided into two groups: one early to initiate radiotherapy group (≤2 cycles of immunotherapy, EAR group) and one deferred radiotherapy group (>2 cycles of immunotherapy, DEF group). The clinical efficacy and adverse reactions were compared between the two groups. Progression-free survival (PFS) and overall survival (OS) were evaluated by Kaplan-Meier curves, the Cox proportional hazard model was used to find out predictors of PFS and OS. Results: The tumor control rates had no significance was observed when comparing these two groups (50.0% and 26.9%, respectively, p = 0.093). The PFS in the RAE group was significantly higher than that in the DEF group (median PFS: 12.2 months vs 5.3 months, P<0.05). The OS in two groups were no significance (median OS: 20.5months vs 23.1months, P>0.05). The results of the Cox multivariate regression analysis revealed that the number of metastatic lesions and organs were independent prognostic factors for PFS. The number of metastatic lesions and organs, maintain therapy were independent predictors associated with OS. All patients well tolerated the treatments. Conclusions: Early initiation of local radiotherapy resulted in better PFS and no significant increase in adverse reactions was observed.

Pathological evaluation of tumor immune microenvironment before first-line anti-PD1 plus anti-angiogenic therapy in patients with unresectable hepatocellular carcinoma (HCC): Towards a prediction for treatment efficacy.

e14662 Background: Immune checkpoint inhibitor (ICI) combined with anti-angiogenic therapy is the standard first-line treatment for unresectable HCC patients. However, most patients do not derive durable benefit and will progress faster. Simultaneously, sufficient clinically validated biomarkers to stratify patients are lacking in HCC. Recent studies have shed a light on the strong connection between immunotherapy efficacy and tumor immune microenvironment (TIME) in HCC. Thus, this study aims to investigate TIME features before treatment to develop a potential way for survival prediction which may optimize risk stratification. Methods: A total of 84 unresectable HCC patients who received first-line ICI plus anti-angiogenic therapy at Nanjing Drum Tower Hospital were included. 4 multiplex immunohistochemistry (mIHC) panels containing 18 biomarkers were developed to thoroughly evaluate immune cells in TIME before therapy, such as cytotoxic T cells, tissue-resident memory T cells, macrophages and neutrophils. TIME features were then extracted from raw image by digital pathology, including cell subpopulation abundance and spatial profiling. We identified a list of TIME features associated with objective response rate (ORR), progression free survival (PFS) and overall survival (OS), and developed a TIME-based risk score (TIS) in our cohort using machine-learning. Results: After data cleaning, a total of 78 patients with complete clinical information and TIME features were included and split into training and validation sets. A higher positive rate of CD103+ cells and CD8+ cells were observed in responder, while patients with higher CD66b+ positive rate showed shorter PFS and OS. In terms of spatial profiling, tumor cells accompanied with more CD8+ cells were associated with longer PFS and OS, while longer distance from CD14+ cells and CD66b+ cells to tumor cells favored longer PFS and OS. Regarding PFS prediction, our machine-learning model TIS included both immune cell abundance and spatial features. Stratifying patients in the low- and high-risk groups using TIS revealed prolonged PFS (p<0.0001, HR: 0.24, 95%CI [0.13-0.45]) and OS (p = 0.00057, HR: 0.27, 95%CI [0.12-0.60]) in TIS low-risk group. Moreover, ORR in TIS low-risk group was 52.9% (17/34) and 15.9% (7/44) in TIS high-risk group. Univariable and multivariable analysis demonstrated that TIS was an independent predictor for ORR (p = 0.0017), PFS (p = 0.00065) and OS (p = 0.00042). Independent validation is still awaited. Conclusions: This study demonstrates that our machine-learning based risk score can improve treatment response and survival prediction using TIME features, which provides the potential to optimize risk stratification before first-line treatment for unresectable HCC patients.

1p and 1q: Partners in crime in multiple myeloma.

7571 Background: Cytogenetic abnormalities in multiple myeloma (MM) highly influence the disease course, response to treatment and survival. Trisomies and immunoglobulin H chain translocations are primary CA while del(17p), gain(1q), del(1p) among others are secondary CA. Gain (3 copies) and amplification (>3 copies) 1q have been recognized as adverse prognostic markers and incorporated into the second revision of the International Staging System (R2-ISS). However, the role of del(1p) is less well defined, especially in the era of novel therapies. We aimed to analyze the outcomes of newly diagnosed MM (NDMM) patients with chromosome 1 abnormalities, mainly del 1p, treated with autologous stem cell transplant (ASCT) consolidation at our institution. Methods: We conducted a retrospective study of all NDMM patients who were treated with ASCT from 1/1/2015-2/13/2019 (n=511). High-risk cytogenetics (HRC) were defined by the presence of del(17p), t(4;14), or t(14;16) similar to R-ISS; standard-risk cytogenetics (SRC) were defined as the absence of HRC. Modified HR cytogenetics (mHRC) included gain/amp 1q and/or t(14;20) in addition to HRC, while ultra high-risk (uHRC) included 2 or more mHRC CA. Results: Of 511 pts transplanted, 453 had cytogenetic data at the time of diagnosis. SRC were seen in 353 pts (77.9%), while 100 (22.1%) had HRC, 156 (34.4%) had mHRC, and 43 (9.5%) had uHRC. Thirty-two (7.1%) pts had del(1p) while 105 (23.2%) had gain 1q and 30 (6.6%) had amplification 1q. As expected, compared to SRC pts, pts with HRC, mHRC and uHRC had higher risk of relapse or death. Patients with gain and amp 1q had inferior outcomes in terms of progression-free survival (PFS) (HR 1.35; 95% CI 1.06-1.73, p=0.016), time to next treatment (TTNT) (HR 1.84; 95% CI 1.40-2.42, p<0.001) and overall survival (OS) (HR 1.47; 95% CI 1.06-2.02, p=0.02) compared to those without, consistent with published literature. The median PFS, TTNT and OS from ASCT in pts with gain/amp 1q were 3.17 years (y), 3.95y and 7.13y, respectively, compared to 4.01y, 7.60y and 8.21y in pts without gain/amp 1q. Pts with del(1p) had inferior PFS (median 2.43y versus 3.98y; HR 1.75; 95% CI 1.16-2.64, p=0.008), TTNT (median 2.72y versus 6.17y; HR 1.96; 95% CI 1.22-3.14, p=0.005) and OS (median 4.11y versus 8.38y; HR 2.19; 95% CI 1.34-3.58, p=0.002) from the time of ASCT compared to those without del(1p). Conclusions: In our study of NDMM patients that underwent AHCT, del(1p) at diagnosis was an independent predictor of shorter PFS, TTNT and OS. Despite induction therapy involving novel drugs and ASCT consolidation, patients with del(1p) at diagnosis continue to have inferior outcomes. Larger analyses are needed to validate the prognostic value of del(1p) and investigate its role in predicting outcomes in MM.

High pre-treatment NLR and PLR predict poor prognosis of patients with recurrent/metastatic head and neck squamous cell carcinoma treated with immune checkpoint inhibitors.

e18001 Background: The treatment landscape of unresectable recurrent and/or metastatic (R/M) Head and Neck Squamous cell Carcinoma (HNSCC) has profoundly changed with the introduction of Immune checkpoint inhibitors (ICIs). High neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been associated with poor outcome in several tumor types. The aim of the present study was to investigate the role of pre-treatment NLR and PLR in predicting overall survival (OS) of patients treated with ICIs. Materials and Methods: We retrospectively reviewed the clinical records of 106 consecutive patients with R/M-HNSCC who received ICIs (single-agent or ICIs-based treatment) between January 2018 and June 2023 at the Istituto Oncologico Veneto of Padua. Patients were grouped into platinum-refractory (patients progressed within 6 months from the last platinum dose) and platinum-sensitive. The cut-off values of pre-treatment NLR and PLR were determined based on percentile distribution (75th percentile). OS was estimated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used to compare survival outcomes. Results: A total of 102 patients were analyzed. Four patients were excluded because of incomplete data. Primary tumor sites were oropharynx (37%), oral cavity (24%), hypopharynx (19%), larynx (15%), nasopharynx (5%) and nasal cavity (1%). 63 patients (62%) with platinum-refractory disease received nivolumab single-agent. All 39 patients (38%) with platinum-sensitive disease were PD-L1 positive (CPS≥1) and received pembrolizumab-based treatment. Median OS was 8.0 months (95% CI 5.8-10.1) in the platinum-refractory cohort and 13.3 months (95% CI 7.3-19.3) in the platinum-sensitive cohort. At the univariate analysis high NLR (≥7) and PLR (≥345) correlated with poor OS in the overall population and in both the platinum-refractory and the platinum-sensitive cohorts (Table1). At the multivariate analysis PLR was an independent predictor of OS. Conclusions: The efficacy results reported in this retrospective series were in line with the literature data. High PLR was an independent predictor of poor outcome regardless of the platinum sensitivity. Prospective studies are needed to better explore the predictive role of easily obtainable blood biomarkers in this poor prognostic population. Univariate analysis for OS [Table: see text]

Prognostic Impact of Mucin Expression in Curatively Resected Ampulla of Vater Cancer.

Introduction: Mucins play a pivotal role in epithelial carcinogenesis; however, their role remains elusive in ampulla of Vater (AoV) cancer, regardless of histological subtype. Therefore, we investigated the clinical significance of MUC1, MUC2, MUC5AC, and MUC6 expression in AoV cancer. Methods: Using samples from 68 patients with AoV cancer, we performed immunohistochemical staining for MUC1, MUC2, MUC5AC, and MUC6 using a tissue microarray. Subsequently, we analyzed their expression patterns in relation to clinicopathological parameters and patient outcomes. Results: Of the patients, 98.5% exhibited positive expression for MUC1, while MUC2, MUC5AC, and MUC6 were expressed in 44.1%, 47.1%, and 41.2% of the patients, respectively. Correlation analyses between mucin expression and clinicopathological factors revealed no significant associations, except between MUC5AC expression and N stage. Univariate analysis demonstrated significant associations between MUC5AC expression and overall survival (OS). Multivariate analysis further confirmed that MUC5AC expression was a significant predictor of OS, along with the N stage. However, MUC5AC expression was not meaningfully associated with recurrence-free survival (RFS). The patients positive for MUC5AC expression had a considerably shorter OS than those with negative expression. Conclusions: Our study provides insights into the clinical impact of mucins on AoV cancer, regardless of the histological subtype. Although MUC1 expression is universal, MUC5AC expression is a significant prognostic indicator that correlates with lymph node metastasis and poor OS. These results emphasize the possible utility of MUC5AC as a biomarker for extensive lymph node dissection and the prognostic evaluation of patients with AoV cancer.

Exploring racial disparities and tumor characteristics of CA19-9 producer and non-producer among patients with advanced pancreatic ductal adenocarcinoma (PDAC): Implications for survival and personalized treatment strategies.

e16309 Background: Despite substantial progress in cancer treatment, PDAC remains a highly lethal disease. CA19-9 plays a crucial role in PDAC diagnosis and therapeutic response assessment. We aimed to evaluate racial differences, tumor characteristics, and outcomes between CA19-9 non-producers and producers among advanced PDAC patients (pts) at an academic teaching hospital. Methods: A retrospective analysis was conducted in patients with unresectable or metastatic PDAC treated at Mount Sinai Health System between January 2012 and December 2021. Pts were categorized into two groups based on CA19-9 levels, using a threshold of 37 U/mL: CA19-9 non-producers (≤37 U/mL) and CA19-9 producers ( > 37 U/mL). Demographic and clinical data were compared between the two groups, and the association between CA19-9 levels and overall survival (OS) was assessed using Kaplan-Meier estimates and multivariable Cox proportional hazards regression models. Results: A total of 238 pts were included in the analysis, with a median age of 67 years and a balanced gender distribution (52% male). The cohort comprised locally advanced (29.8%) and metastatic (70.2%) cases, with a diverse ethnic composition including non-Hispanic whites (37%), non-Hispanic blacks (25%), and Hispanics (18%). Among the pts, 23.5% were CA19-9 non-producers, while 76.5% were CA19-9 producers. Significant racial differences were observed, with non-Hispanic blacks more likely to be CA19-9 non-producers compared to non-Hispanic whites ( P< 0.001). However, no statistically significant differences were found in age, smoking status, tumor location, size, or site of metastasis between the two groups. Median overall survival (OS) was 13m for CA19-9 producers and 16m for non-producers, but this difference was not statistically significant in both univariate and multivariate analyses (HR 1.09, 95% CI 0.74-1.58, P = 0.66; HR 1.06, 95% CI 0.72-1.58, P 0.8). Hispanic ethnicity was correlated with improved OS (HR 0.59, 95% CI 0.36-0.95, P = 0.029), while larger tumor size predicted worse OS (HR 1.17, P < 0.001). Conclusions: This study highlights racial disparities in CA19-9 production among locally advanced and metastatic PDAC patients. Despite observed differences, CA19-9 levels alone did not emerge as a statistically significant predictor of OS. Future research should delve deeper into the racial disparities observed in CA19-9 production, exploring underlying biological mechanisms and potential implications for diagnostic and therapeutic approaches as this could refine our understanding of PDAC, facilitating targeted interventions for improved patient outcomes.

Scrutinizing prognostic scores’ effectiveness in non-Hodgkin’s lymphomas with primary lymph node involvement

Introduction. Non-Hodgkin lymphoma (NHL) encompasses a diverse group of malignancies arising from malignant proliferation of lymphocytes, each subtype characterized by unique epidemiological, etiological, and clinical features. Prognostication is essential for guiding treatment decisions and improving patient outcomes. Prognostic scores, including traditional and molecular systems, offer insights into survival prediction. The aim of the present study was to evaluate the applicability of traditional prognostic scores based on clinical markers and laboratory biomarkers in predicting the outcomes of patients with primary nodal NHL. Materials and methods. This study included 78 NHL patients treated at the Chisinau Oncological Institute from 2017 to 2021. Clinical and biological data were collected, and the following prognostic scores were calculated: International Prognostic Index (IPI), The combined index of hemoglobin, albumin, lymphocyte, and platelet (HALP score), Platelet to Lymphocyte Ratio (PLR), Neutrophil to Lymphocyte Ratio (NLR), Albumin/Globulin ratio (AG), and Charlson comorbidity index (CCI). Statistical analyses, including descriptive statistics, ROC curve analysis, and Kaplan-Meier survival curves, were conducted. Results. Of the patients, 40 (51.2%) were female, with a mean age of 57.1 ± 10.2 years. Peripheral lymph nodes were predominantly affected (84.6%), with diffuse large B-cell lymphoma being the most prevalent subtype (59.0%). Prognostic scores, including the International Prognostic Index (IPI), Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score, and Charlson Comorbidity Index (CCI), demonstrated varying levels of discriminatory ability in predicting overall survival (OS). Notably, the HALP score (AUC = 0.650; p = 0.026), IPI (AUC = 0.745; p = 0.0002), and CCI (AUC = 0.636; p = 0.043) were statistically significant predictors of OS. Conclusions. Traditional prognostic scores (IPI. HALP score, CCI) offer valuable prognostic information for NHL patients. Further research is needed to validate these findings and explore cost-effective prognostic strategies.

CASTOR1 phosphorylation as a predictor of survival in male patients with KRAS-mutated lung adenocarcinoma.

e20015 Background: Lung cancer, a leading global cause of cancer-related mortality, necessitates enhanced prognostic markers for improved treatment outcomes. This study focuses on the predictive value of phosphorylated cytosolic arginine sensor for mTORC1 subunit 1 at S14 (pCASTOR1) in lung adenocarcinoma (LUAD) patients, specifically in males with KRAS mutations. Methods: This retrospective study, approved by University of Pittsburgh IRB, utilized formaline-fixed paraffin embedded primary tissues from two independent cohorts of patients who underwent thoracic surgical procedures at the University of Pittsburgh Medical Center (UPMC) from 2002 to 2011. Comprehensive clinical, demographical and pathological information was obtained from UPMC Cancer Registry, with cases lacking incomplete information excluded from analysis. Study endpoints included overall survival (OS) and relapse-free survival (RFS). An antibody targeting pCASTOR1 was employed to analyze LUAD tumor and adjacent non-tumor lung tissues from both cohorts. A pathologist, blinded to patient information and survival outcomes, conducted scoring in 5% increments. Scores were categorized as low or high pCASTOR1 based on second or third quartile. Correlations between pCASTOR1 scores and OS/RFS were examined, stratifying by clinical, pathological, demographic, or genotype data. Univariate OS and RFS analyses were conducted using the Kaplan-Meier method and log-rank test, while multivariate survival significance was assessed via Cox regression analysis. Additionally, unpaired T-tests were utilized to compare pCASTOR1 levels between non-tumor and tumor cells. A significance threshold of p < 0.05 was applied for all analyses. Results: Tumor cells exhibited significantly elevated pCASTOR1 scores compared to non-tumor cells in both cohorts (P < 0.05). High pCASTOR1 scores predicted poor OS (HR = 3.3, P = 0.0008) and RFS (HR = 3.0, P = 0.0035) in male patients with KRAS mutations in Cohort 1. pCASTOR1 remained an independent predictor for OS (HR = 4.1, P = 0.0047) and RFS (HR = 3.5, P = 0.0342) after controlling for other factors. Cohort 2, comprised solely of smokers with incomplete genotype information, validated these findings, with high pCASTOR1 scores correlating with worse OS (HR = 4.8, P = 0.0363). Notably, in early-stage LUAD, elevated pCASTOR1 scores were associated with significantly worse OS (HR = 3.3, P = 0.0176) and RFS (HR = 3.1, P = 0.0277) in male patients with KRAS mutations in Cohort 1, and worse OS (HR = 5.0, P = 0.0069) and RFS (HR = 5.0, P = 0.0069) in Cohort 2, akin to late-stage patients. Conclusions: Elevated pCASTOR1 score serves as a robust biomarker predicting poor OS and RFS in male LUAD patients with KRAS mutations, offering potential clinical utility in optimizing treatment strategies for this subgroup.

The efficacy and safety of furmonertinib in patients with advanced EGFR-mutated NSCLC and leptomeningeal metastases.

e20525 Background: Leptomeningeal metastasis (LM) is a common and fatal complication in patients with advanced non-small-cell lung cancer (NSCLC) harboring epidermal growth factor receptor ( EGFR) mutation. This retrospective study aimed to evaluate the efficacy and safety of furmonertinib in patients with advanced EGFR-mutated ( EGFRm) NSCLC and LM. Methods: Eligible patients with confirmed advanced EGFRm NSCLC and LM were treated with furmonertinib. The primary endpoints were LM response rate and progression-free survival (PFS). Secondary endpoints were overall survival (OS) and adverse events (AEs). Results: This retrospective study analyzed the efficacy and safety of 31 EGFRm advanced NSCLC patients with LM at two hospitals between February 2020 to March 2023. The median age was 56 years (rang: 31-75), 22 (71.0%) were females. 19 (61.3%) patients had ECOG PS≥2 and all 31 patients (100%) had adenocarcinoma histology. For the treatment of LM, 19 (61.3%) patients received furmonertinib as first-line treatment, 8 (25.8%) patients as second-line treatment. 16 (51.6%) patients were treated with 240 mg of furmonertinib and 12 (38.7%) patients with 160 mg of furmonertinib. The median follow-up duration was 16.80 months (95% CI 12.71-20.89 months). LM objective response rate (ORR) was 75.0% and LM disease control rate (DCR) was 95.0% according to RANO-LM radiologic criteria. Overall ORR was 22.6% and DCR was 96.8%. Median LM duration of response (DoR) was 12.00 months (95% CI 7.40-16.60 months) and median overall DoR was 7.20 months (95% CI 3.60-10.80 months). 23 (74.2%) of the 31 patients had progressed or died by data cutoff. The median PFS was 11.70 months (95% CI 9.48-13.92 months) and the median OS was 18.40 months (95% CI 12.49-24.21 months). There was no significant difference in survival (median PFS: 11.70 months vs 10.90 months, p = 0.335; median OS: 18.40 months vs 13.50 months, p = 0.196) between the 19 patients who treated with furmonertinib as first-line therapy and those who treated with furmonertinib as second-line therapy. Although data on cerebrospinal fluid (CSF) clearance were not available, we observed improved neurologic function in 18 (75%) of 24 patients with baseline neurologic abnormalities. Logistic regression analysis showed that the therapeutic dose of furmonertinib was a positive predictor of OS in NSCLC patients harboring EGFR mutation with LM [HR: 2.679 (1.004-7.147), P = 0.049]. The most common AEs were rash, diarrhea and decreased appetite. However, most AEs were grade 1-2. Conclusions: Our study provides real-world clinical evidence that furmonertinib shows an encouraging efficacy and a manageable safety profile in patients with EGFRm NSCLC and LM.

Effect of perioperative medical therapy on prognosis in recurrent nasopharyngeal carcinoma: A comparative effectiveness research.

e18051 Background: Transnasal endoscopic (TEN) surgery has evolved to be an important treatment for rNPC.The role of perioperative chemotherapy or immunotherapy has not been determined yet. Methods: Three single arm, prospective researches were pooled to analyze the comparative effectivenessof neoadjuvant, adjuvant therapy and surgery only in rNPC patients undergoing TEN surgery through 2019 to 2023. Data was collected including sex, age, TNM staging, treatment modality and internal carotid artery (ICA) management in three investigator initial trials (NCT05011227, ChiCTR1900026341, NCT05350891). The primary and secondary outcomes were overall survival (OS) and local recurrence free survival (LRFS). Statistical analysis was performed using SPSS 29.0 (IBM).Variables with two-sided P-values <0.05 in log-rank tests were identified as significant. Multivariable Cox regression analysis was conducted to reveal the prognostic value of treatment modality. Results: Overall, 233 eligible participants were divided into three treatment groups (neoadjuvant, adjuvant, and surgery only group). The clinicopathological characteristics were balanced (Table). In a mean follow-up period of 605 days, the 1-year, 2-year OS rate were 91.9%, 83.3% respectively. According to Kaplan Merier survival analysis, immunotherapy± chemotherapy after surgery significantly improved OS compared with surgery only (P<0.001). Although no significance (P=0.176) was noted in neoadjuvant compared with surgery only group, partially because of the small sample size, the 1-,3-year OS rate was much higher. When blended together, neoadjuvant+adjuvant group also won over surgery only group regarding OS (P<0.001) and LRFS (P=0.002). Subgroup analysis also indicated that age≥52 (P=0.002), higher T staging (P<0.001), and embolization of ICA (P<0.001) were associated with worse prognosis. Sex showed no significant effect on survival (P=0.533). The above four factors were adopted for multivariate COX analysis, elucidating that age (P=0.005), T staging (P=0.024) and treatment modality (P=0.007) were independent predictor for OS, however, embolization of ICA (P=0.097) was not. Conclusions: Adjuvant therapy, as an independent predictor of OS, improved the overall survival in rNPC patients underwent TEN surgery. The efficacy of neoadjuvant therapy demanded solid evidence from larger sample size cohort. Clinical trial information: NCT05011227 , NCT05350891 , ChiCTR1900026341. [Table: see text]

Radiomic survival prediction with liver metastases in colorectal cancer.

e15584 Background: The survival outcome of colorectal cancer depends upon staging and the presence of metastases. Nonetheless, there isn’t a reliable prediction model for overall survival (OS) specifically tailored to patients with colorectal cancer who have liver metastases. Consequently, this study aims to find radiomic features that can be utilized to predict OS of colorectal cancer with liver metastases. Methods: We utilized the Colorectal Liver Metastases data set in The Cancer Imaging Archive (TCIA). Overall, 197 patients with colorectal cancer metastatic to the liver were identified. Semi-automatic segmentation of liver metastases was used to extract radiomic features including Gray-Level Co-occurrence (glcm), Gray-Level Run Length Matrix (glrlm), Gray-Level Size Zone Matrix (glszm), Gray-Level Dependence Matrix (gldm), and Neighborhood Gray-Tone Difference Matrix (ngtdm). 3D Slicer was used to extract radiomic features. We tested a Cox proportional hazards model in each radiomics feature to predict OS. Results: Total 107 radiomic features were extracted from pre-segmented liver metastases on patients’ Computed Tomography images. Among them, original shape sphericity, original glcm correlation, original gldm DependenceEntropy, and original glrlm RunEntropy were statistically significant for the prediction of OS, with a hazard ratio of -2.16 (CI 0.01-0.92; p value 0.04), 1.54 (CI 1.5-14.0; p value 0.006), 0.51 (CI 1.0-2.5; p value 0.02), and 0.52 (CI 1.0-2.6; p value 0.03), respectively. Conclusions: Our data analysis indicates crucial radiomic features that hold promise for predicting the clinical outcome of patients with colorectal cancer who have liver metastases. Future research with a larger sample size is warranted for the external validation of our results.

The utility of multiple clinical variables in predicting survival outcome for patients with rectal cancer: An integrated regression and retrospective cohort analysis.

e15610 Background: Prior studies have investigated clinical factors impacting the survival rates of rectal cancer patients. However, a robust and precise model for discerning these risks, which can be identified by integrated regressions analysis has yet to be established. The aim of this study is to develop and evaluate the diagnostic value of the constructed prediction model based on selected clinical variables. Methods: Patients diagnosed with stage II-III rectal cancer (April 2015-June 2021) were retrospectively enrolled as the primary cohort. Individual variables were extracted and then subjected to a K-adaptive partitioning algorithm for cut-off point determination and grouping. The Cox and least absolute shrinkage and selection operator regression (LASSO) regression were applied for independent predictors selection over significant overall survival (OS), and a nomogram was subsequently constructed. The performance of the constructed model was evaluated using the receiver operating characteristics (ROC) curves, calibration curves, and decision curve analysis (DCA), and stepwise compared with data cohorts derived from TCGA and SEER databases. Results: The Cox-LASSO analysis results considered the four independent variables as significant predictors, yielding the risk score equation: 1.086(for CEA level≥7.5 ng/ml) -1.7756(if gender is male) +1.829*(pT stages) +0.582*(pN stages). Notably, the distal resection margin (DRM) was excluded from the final model following the analysis (p = 0.060, 95%CI: -0.04-2.17). The constructed model (C-index:0.790, 95%CI: 0.673-0.743, AUC:0.873) outperformed the conventional TNM staging models (C-index:0.539, 95%CI:0.121-0.957, AUC:0.735). It stratified patients into low- or high-risk groups with significant OS differences (93% vs. 37%, p≤0.0001, respectively). The calibration curves for OS probability showed strong homogeneities between predictions and actual observations. DCA revealed positive net benefits at evaluated first, third, and fifth years. Moreover, the external validations confirmed the accurate prediction following the constructed model, with AUC of 0.745 and 0.705 for the TCGA and SEER datasets, respectively. Conclusions: This study resulted in a novel and effective prediction model for rectal cancer patients based on conventional clinical characteristics. It demonstrated solid performance and can serve as a convenient tool for OS prediction, aiding in rectal cancer patients' risk scoring and clinical decision-making.