Significant Differences In Survival Outcomes Research Articles

Bladder transitional cell carcinoma anatomic primary site as a predictor of survival and mortality: a population-based retrospective cohort study

Background: Bladder cancer is a heterogeneous disease with varying prognostic outcomes based on the primary tumor site within the bladder. This study aims to evaluate the impact of tumor location on overall survival and cancer-specific survival in bladder cancer patients. Methods: The authors conducted a retrospective cohort study using data from the Surveillance, Epidemiology, and End Results database. Patients with primary transitional cell carcinoma of the bladder were categorized based on their tumor locations. Survival outcomes were assessed using Kaplan–Meier analysis and Cox proportional hazards regression models, adjusted for age, sex, race, cancer stage, and treatment modalities. Additionally, binary logistic regression models were employed to predict overall mortality (OM) and cancer-specific mortality (CSM) at 1, 5, and 10 years. Results: The study included 107 909 patients diagnosed with primary bladder cancer between 2000 and 2021. Significant differences in survival outcomes were observed across different tumor sites. Bladder cancer originating in the urachus had the worst OS before 100 months and the worst CSS overall. Tumors in the anterior wall showed the worst OS after 100 months. In the Cox multivariable analysis, anterior wall tumors were associated with a 1.513-fold increased risk of death compared to lateral wall tumors. The binary logistic regression models showed that anterior wall tumors predicted the highest OM and CSM at 1-year, while urachal tumors had the worst outcomes at 5 and 10 years. Conclusions: The primary site of bladder cancer is a significant predictor of survival outcomes, with tumors in the urachus and anterior wall associated with a poorer prognosis. These findings underscore the importance of considering tumor location in the prognosis and management of bladder cancer. Future studies should aim to validate these findings in more diverse populations and explore the underlying biological mechanisms that drive these differences.

Machine learning-based individualized survival prediction model for prognosis in osteosarcoma: Data from the SEER database.

Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple machine learning (ML) models with the traditional Cox proportional hazards (CoxPH) model in predicting prognosis and explored the potential of ML models in clinical decision-making. From 2000 to 2018, 1243 patients with osteosarcoma were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Three ML methods were chosen for model development (DeepSurv, neural multi-task logistic regression [NMTLR]) and random survival forest [RSF]) and compared them with the traditional CoxPH model and TNM staging systems. 871 samples were used for model training, and the rest were used for model validation. The models' overall performance and predictive accuracy for 3- and 5-year survival were assessed by several metrics, including the concordance index (C-index), the Integrated Brier Score (IBS), receiver operating characteristic curves (ROC), area under the ROC curves (AUC), calibration curves, and decision curve analysis. The efficacy of personalized recommendations by ML models was evaluated by the survival curves. The performance was highest in the DeepSurv model (C-index, 0.77; IBS, 0.14; 3-year AUC, 0.80; 5-year AUC, 0.78) compared with other methods (C-index, 0.73-0.74; IBS, 0.16-0.17; 3-year AUC, 0.73-0.78; 5-year AUC, 0.72-0.78). There are also significant differences in survival outcomes between patients who align with the treatment option recommended by the DeepSurv model and those who do not (hazard ratio, 1.88; P < .05). The DeepSurv model is available in an approachable web app format at https://survivalofosteosarcoma.streamlit.app/. We developed ML models capable of accurately predicting the survival of osteosarcoma, which can provide useful information for decision-making regarding the appropriate treatment.

Prognostic Impact of Tumor Growth Rate During Second-line Chemotherapy in Patients With Gastric Cancer.

Despite the remarkable developments in chemotherapy for gastric cancer (GC), rapid tumor growth is sometimes experienced during chemotherapy. This study investigated the association of tumor growth rate (TGR) during second-line chemotherapy with the prognosis of patients with GC. We retrospectively reviewed 29 patients with GC treated with nab-paclitaxel plus ramucirumab as second-line chemotherapy between 2017 and 2019 at Osaka Metropolitan University. Of them, 13 cases with target lesions were classified into two groups according to TGR using a cutoff value of 0.25. Clinicopathological factors and survival outcomes were compared between the high TGR (n=5) and low TGR (n=8) groups. The median duration of first-line chemotherapy was significantly longer in the high TGR group than in the low TGR group [median 298 days vs. 72.5 days, p=0.030]. Progressive disease (PD) was observed in 60% of patients with high TGR, whereas stable disease (SD) was observed in 75% patients with low TGR. The median survival time (MST) after starting chemotherapy was 488 days in the low TGR group but was not reached in the high TGR group (log rank p=0.215). The MST after PD was 145 days in the low TGR group but was not estimated in the high TGR group (log rank p=0.345). Based on the absence of significant differences in survival outcomes between the high and low TGR groups, sequential late-line chemotherapy might be considered important, even for patients with high TGR.

Medial opening wedge high tibial osteotomy performs similarly irrespective of body mass index.

This study investigates the effect of the body mass index (BMI) on the early (2 years) to midterm (5 years) results of medial opening wedge high tibial osteotomy (MOWHTO). A prospectively maintained single-centre database of 1138 knee osteotomies, between 2002 and2022, was retrospectively reviewed. Adult patients who underwent MOWHTO for symptomatic unicompartmental medial knee osteoarthritis (OA), with varus knee malalignment, having failed conservative management, were included. Patients were categorized into threegroups according to their BMI as per the classification from the National Institute for Health and Care Excellence (NICE): the healthy weight (HW) group (BMI of 18.5-24.9 kg/m2), the overweight (OW) (BMI of 25-29.9 kg/m2), and the obesity (OB) group (BMI ≥ 30 kg/m2). Multiple patient-reported outcome measures (n = 6) were recorded preoperatively and at 2 and 5 years postoperatively. Deformity analysis was undertaken preoperatively and postoperatively. The relative risk (RR) of the complications between the HW, OWand OB groups was calculated. The rate of conversion to arthroplasty, and 5and 10 years survivorship were recorded, as well as the hazard ratio (HR) of BMI on survivorship. A total of 574 cases were included in the study: the HW group (n = 96), the OW group (n = 233)and the OB group (n = 245), with a mean BMI of 23 ± 1.5 kg/m2, 27.4 ± 1.4 kg/m2 and 34.4 ± 3.8 kg/m2, respectively. The mean follow-up was 13.3 years (4.8-20.3). The mean mechanical tibiofemoral angle corrections were in the HW group: 7.1 ± 3°, OW group: 6.6 ± 3.5°and OB group: 7.1 ± 3.8°, with no intergroup significant difference (p = n.s.). Clinically, despite lower preoperative scores in the OW and OB groups, no difference was observed postoperatively amongst the three groups. The overall complication rate was 12.5% in the HW group, 6.8% in the OW group, and 9.8% in the OB group. There was no significant difference in the RR of complications between the HW and OW groups (RR = 0.6, 95% confidence interval [CI] = 0.3-1.3)(p = 0.2), and the HW and OB groups (RR = 0.8; 95% CI = 0.3-2.2)(p = 0.7). There was no overall significant difference in survival outcomes based on the BMI between the threegroups (p = 0.4). The HR of conversion to arthroplasty between the HW and OW groups was 1.4 [95% CI = 0.6-3.5](p = 0.5)and between the HW and OB groups was 1.8 [95% CI = 0.8-4.4] (p = 0.2). BMI has no significant effect on either the radiological corrections, clinical outcomes, complicationsor survivorship of MOWHTO at short- to medium-term follow-up. No specific cutoff point for BMI can be recommended as a contraindication to MOWHTO. Level IV, Retrospective cohort study.

High-grade B-cell lymphoma, not otherwise specified: CNS involvement and outcomes in a multi-institutional series

AbstractLittle is known about the central nervous system (CNS) risk in high-grade B-cell lymphoma, not otherwise specified (HGBL NOS). Hence, we sought to describe the rates of baseline CNS involvement, risk of CNS recurrence after primary therapy, and management strategies in HGBL NOS. In this multicenter retrospective study, we included 160 adults with newly diagnosed HGBL NOS treated between 2016 and 2021 at 20 US institutions. Eleven patients (7%) had baseline CNS involvement at diagnosis (leptomeningeal = 6, parenchymal = 4, and both = 1). Baseline CNS involvement was significantly associated only with MYC rearrangement (OR = 3.5) and testicular (in men) or female pelvic (in women) involvement (OR = 8.1). There was no significant difference in survival outcomes between patients with HGBL NOS with (median PFS = 4 years) or without (median PFS = 2.4 years) baseline CNS involvement (P = 0.45). The cumulative incidence of CNS recurrence at 3 years was 11%. Patients with baseline CNS involvement were at the highest risk (48.5% vs 8% for those without baseline CNS involvement) and were excluded from the risk factors analysis for CNS recurrence. The risk for CNS recurrence was significantly associated with blood or bone marrow involvement, CD5 expression, non–germinal center B-cell subtype, and “dual-expresser lymphoma” phenotype, however, high CNS IPI was not. The prognosis of relapsed HGBL NOS was poor, regardless of whether recurrence was systemic or limited to the CNS, and with currently available salvage strategies, including autologous transplantation and chimeric antigen receptor T-cell modalities, almost all patients with CNS recurrence ultimately succumbed to their disease.

Pan-immune-inflammation value: a new prognostic index in epithelial ovarian cancer

BackgroundEpithelial ovarian cancer (EOC) is one of the deadliest gynaecological malignancies worldwide. The aim of this retrospective study was to create a predictive scoring model based on simple immunological and inflammatory parameters to predict overall survival (OS) and progression-free survival (PFS) in patients with EOC.MethodsWe obtained 576 EOC patients and randomly assigned them to the training set (n = 405) and the validation set (n = 171) in a ratio of 7:3. We retrospectively evaluated the association between PIV and OS and PFS using a novel immunoinflammatory marker, according to the optihmal treshold of PIV, we divided the patients into two different subgroups, high PIV (PIV > 254.9) and low PIV (PIV ≤ 254.9). Pan-immune Inflammatory Value (PIV) was computed as follows: neutrophil count (109/L) × platelet count (109/L) × monocyte count (109/L)/lymphocyte count (109/L). Then developed a simple score prediction model based on several independent prognostic parameters using Cox regression analysis. We used receiver operator characteristic (ROC) curves, calibration plots, and decision analysis (DCA) curves to evaluate the performance of the model. Finally, we used Kaplan-Meier curves to ensure that the model could distinguish well between low- and high-risk groups.ResultsThere was a significant difference in survival outcomes between high PIV (PIV > 310.2) and low PIV (PIV ≤ PIV310.2) (3-year survival rates of 61.34% and 76.71%, respectively); 5-year OS, 25.21% and 51.14%, respectively; 3-year PFS, 40.90% and 65.30%; 5-year PFS, 19.33% and 39.73%, respectively). Column plots of OS and PFS were constructed using independent prognostic factors. In the training module, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.713, 0.796, 0.839, and 0.730, 0.799, 0.826, respectively.In the validation cohort, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.676, 0.803, 0.685, and 0.700, respectively, 0.754, 0.727. The calibration curves showed good agreement between predicted survival and actual observations. The decision analysis curves also showed that the current model has good accuracy and clinical applicability. 3-year OS was 61.34% and 76.71%, respectively; 5-year OS was 25.21% and 51.14%, respectively; 3-year PFS was 40.90% and 65.30%, respectively; 5-year PFS was 19.33% and 39.73%, respectively.ConclusionsWe constructed and validated a PIV-based nomogram to predict OS and PFS in EOC patients, with a view to helping gynaecologists converge on oncologists in their treatment and follow-up expertise in epithelial ovarian cancer.

Progression patterns, resistant mechanisms and subsequent therapy for ALK-positive NSCLC in the era of second-generation ALK-TKIs

BackgroundIn the era of second-generation ALK tyrosine kinase inhibitors (ALK-TKIs), there was a paucity of data regarding the progression patterns, resistant mechanisms, and subsequent therapeutic approaches for ALK-positive (ALK+) non-small cell lung cancer (NSCLC).MethodsPatients with advanced ALK+ NSCLC were retrospectively selected from our center. Cohort 1 consisted of patients who experienced disease progression after receiving first-line alectinib treatment (n = 20), while Cohort 2 included patients who progressed following sequential treatment with crizotinib and second-generation ALK-TKIs (n = 53). Oligo-progression was defined as the occurrence of disease progression in no more than three lesions. Symptomatic progression was determined when patients developed new symptoms or experienced worsening of pre-existing symptoms during radiological progression.ResultsThe incidence of central nervous system (CNS) progression and symptomatic CNS progression was significantly lower in Cohort 1 compared to patients treated with crizotinib, with rates of 15.0% vs. 56.6% (p = 0.002) and 5.0% vs. 32.1% (p = 0.016), respectively. A total of 60.3% (44/73) patients underwent repeated biopsy and next-generation sequencing subsequent to the second-generation ALK-TKI resistance, with secondary mutation in ALK kinase domain emerging as the predominant mechanism of resistance (56.8%). Local therapy was applied to 50% of oligo-progression cases. Subsequent ALK-TKIs demonstrated significantly prolonged progression-free survival (PFS) (8.6 m vs. 2.7 m, p = 0.021, HR = 0.43, 95%CI: 0.15–0.85) and long-term overall survival (OS) (NA vs. 11.9 m, p = 0.132, HR = 0.50, 95%CI: 0.18–1.25) in patients harboring ALK resistance mutations, compared to those without such mutations. For patients without ALK-resistant mutations following progression on second-generation ALK-TKIs, there was no statistically significant difference in survival outcomes between subsequent chemotherapy or alternative ALK-TKI treatments.ConclusionsFirst-line alectinib demonstrated superior efficacy in protecting the CNS compared to crizotinib. For patients with ALK-resistant mutations following the resistance to second-generation ALK-TKIs, appropriate sensitive ALK-TKI should be administered; for those without such mutations, the selection of chemotherapy or third-generation ALK-TKI should be based on the patient’s overall physical health and personal preferences.

A comparative study of double track anastomosis and tubular esophagogastric anastomosis in laparoscopic radical proximal gastrectomy for upper gastric carcinoma.

e16117 Background: For the upper gastric cancer, especially adenocarcinoma at the esophagogastric junction, the optimal surgical method is still controversial. The purpose of the study is to evaluate the safety and clinical effect of double track (DT) anastomosis in laparoscopic radical proximal gastrectomy (LRPG). Methods: A retrospective analysis was conducted involving 243 patients who underwent LRPG in the Department of Gastrointestinal Surgery, Qilu Hospital of Shandong University from Jan. 2017 to Dec. 2020. Patients were divided into tubular esophagogastric (TG) anastomosis group and double track (DT) anastomosis group, according to the digestive tract reconstruction. Their intraoperative conditions, perioperative recovery and postoperative follow-up were compared. Patients were divided into ≥60 and &lt; 60 groups according to age, to analysis the pros and cons of the two surgical methods in different age groups. According to whether or not indocyanine green (ICG) tracer technology was used during the operation, DT group was also divided into ICG group and non-ICG group. Results: Compared with the TG group, the DT group had less volume of gastric tube drainage, shorter gastric tube drainage time and proton pump inhibitors application time, and lower reuse rate of proton pump inhibitors. However, the DT group had more total operation time and lymph node dissection time. The median follow-up time of the patients was 36.0 months. At the end of study, the 1-year OS rate and DFS rate were 94.2% and 92.6% in the TG group and 95.8% and 93.7% in the DT group. The 3-year OS rate and DFS rate were 90.2% and 85.2% in the TG group and 91.9% and 87.7% in the DT group. And there was no significant difference in survival outcomes between the two groups. The DT group had a lower anastomotic stenosis at 3rd month after surgery. Moreover, the incidence of reflux esophagitis and Gerd Q score in the DT group were lower compared with the TG group at 3rd month, 1st year and 3rd year after surgery. In addition, elderly patients had a higher incidence of short-term complications in DT group compared with TG group. In the ICG analysis, the ICG DT group had significantly shorter total operation time and lymph node dissection time, less intraoperative blood loss and more lymph nodes obtained compared with the non-ICG DT group. Conclusions: DT anastomosis is a safe and effective way in LRPG for upper gastric carcinoma. Although the operation time of it is longer than that of TG anastomosis, it has a better anti-reflux effect and reduces the incidence of dysphagia and anastomotic stenosis. In elderly patients, it is important to minimize operative time and better to use TG anastomosis. The application of ICG tracer technique in LRPG has positive significance.

Machine learning identification of hypoxia-related genes and prognostic risk-scoring model for effective survival stratification in hepatocellular carcinoma.

e16261 Background: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality globally, where treatment and prognostic assessment have important implications in clinical practice. Hypoxia, as a common feature within solid tumors, can directly change the tumor microenvironment, which affects the efficacy of cancer treatment and prognosis. In this study, we constructed and validated a hypoxia-based prognostic model using bioinformatics and machine learning. Methods: Two public datasets, GSE14520 and GSE41666, were collected from the Gene Expression Omnibus: (1) HCC tumor tissues compared to adjacent normal tissues (N = 214) and (2) HepG2 cells under normoxic and hypoxic conditions (N = 6). Differential expression analysis was performed to identify HCC characteristic genes and hypoxia-related genes, including their common genes (HCC-Hypoxia Overlap genes, HHOs). Using RNA-seq data of HCC patients (N = 367) from the TCGA Liver Cancer (LIHC) database, univariate Cox regression models were identified, and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm selected hypoxia-characteristic genes for the multivariate survival model. A hypoxia-related risk score was calculated based on the model of these characteristic genes and dichotomized cases into high-risk (HR) and low-risk (LR) groups. The model was validated using liver cancer cases (N = 232) from the International Cancer Genome Consortium database (ICGC-LIRI-JP). Results: Through differential expression analysis of the two datasets, we identified 52 HHOs. Univariate Cox analysis of these HHOs indicated that 21 genes were significantly associated with HCC patient survival. Through LASSO regression analysis, a total of 9 characteristic genes, including CENPA, KIF20A, DLGAP5, HMMR, UPB1, AFM, CABYR, PHLDA2, and N4BP2L1 were ultimately retained in the survival model. Based on these 9 genes, TCGA-LIHC samples were classified into HR and LR groups, and Kaplan-Meier (KM) analysis revealed significant differences in survival outcomes (p &lt; 0.032). Risk scoring of the ICGC-LIRI-JP validation set classified samples into HR and LR. KM analysis showed that the survival times of patients in the HR group were significantly shorter than those in the LR group (p &lt; 0.0001). Receiver Operating Characteristic Analysis analysis of the survival model showed area under the curve values of 0.815, 0.774, and 0.771 at 1, 2, and 3 years, respectively, demonstrating high performance in risk stratification. Conclusions: This study established a prognostic risk-scoring model based on 9 characteristic genes associated with hypoxia. This model can effectively stratify risks among HCC patients and demonstrate excellent performance in predicting survival. These findings may offer new biomarkers and therapeutic targets for the personalized treatment of HCC.

Effects of Adjuvant Chemotherapy on Oncologic Outcomes in Patients With Stage ⅡA Rectal Cancer Above the Peritoneal Reflection Who Did Not Undergo Preoperative Chemoradiotherapy

PurposeThis study aimed to evaluate the effects of adjuvant chemotherapy (AC) on oncologic outcomes for patients with stage IIA upper rectal cancer and to investigate whether AC is associated with improved survival outcomes. MethodsThis retrospective study comprised 432 patients with rectal cancer above the peritoneal reflection who had undergone curative resection without preoperative chemoradiotherapy between 2008 and 2016. This study cohort was divided according to whether AC was received (AC group) or not (no-AC group). Risk factors included obstruction, perforation, poorly-differentiated tumor, lympho-vascular invasion, perineural invasion, resection margin involvement, and < 12 lymph nodes harvested. ResultsAmong the 432 patients, 279 (64.6%) had received AC. The AC group had significantly higher 5-year overall survival (OS) rates than those of the no-AC group (93.2% vs. 84.6%, P = .001). Among patients with ≥ 1 risk factors, the AC group (n = 123) had significantly higher rates of 5-year recurrence-free survival (RFS) (81.6% vs. 64.1%, P = .01) and 5-year OS (88.8% vs. 69.0%, P = .001) than those of the no-AC group (n = 59). No significant difference in survival outcomes was observed between the 2 groups in patients aged > 65 years. ConclusionAC was significantly associated with better 5-year RFS and 5-year OS rates in patients with stage IIA rectal cancer above peritoneal reflection who did not receive preoperative chemoradiotherapy, especially in those with ≥ 1 risk factors.

Evolution and prognostic significance of HER-2 changes from primary to residual disease in patients with HER-2–negative breast cancer receiving neoadjuvant chemotherapy.

583 Background: HER-2 changes during the neoadjuvant chemotherapy has not been thoroughly evaluated. The current study aimed to analyze the HER-2 status changes from primary to residual disease in HER-2 negative patients after neoadjuvant chemotherapy and evaluate its impact in survival outcomes. Methods: HER-2 negative breast cancer patients with residual disease after NACT who had paired pre- and post-therapeutic HER2 testing results were retrospectively analyzed. Data on clinical and pathological characteristics, treatment information, and survival outcomes were collected for all eligible patients. HER2 changes from the primary to residual disease were described and logistic regression were performed to identify factors associated with HER2 changes. The Kaplan–Meier method and multivariate Cox regression were used for survival analysis. Results: 571 HER-2 negative breast cancer patients with residual disease after NACT were enrolled, including HER2-zero (35.2%, n=201) and HER2-low (64.8%, n=370) patients before NAC. The overall rate of HER-2 changes rate was 32.4% (negative to positive 1.1%, low to zero 15.4%, zero to low 15.9%). Among the patients with HER-2-zero before NAC, patients with HER-2 changes (zero to low) were likely to be hormone receptor positive (68.1% vs 36.7%, P&lt;0.0001) and had a higher proportion of patients with Ki-67≤20 (Ki-67≤20 27.5% vs 15.6%, P=0.035). Among the patients with HER2-low before NAC, a higher proportion of hormone receptor negative were observed in HER2 changes patients (low to zero) (31.8% vs 18.4%, P=0.008) and the Ki-67 is relatively high in HER-2 changes patients (Ki-76 &gt; 20 73.9% vs 65.0% P=0.030). Multivariable logistic regression analyses showed patients with hormone receptor positive before NAC were related to underwent HER2-zero transferring to HER2-low (OR, 3.436, P&lt;0.0001). The median follow-up time was 50.0 months. In the HER-2 zero group, HER2 changes (zero to low) was significantly associated with better DFS comparing with constant HER2-zero (HR0.49, P=0.01) after adjustment, with 4-year DFS rate was 80.1%,55.7% (Log-rank P =0.033). Subgroup analysis showed that in the hormone receptor positive subgroup, patients with HER2 zero to low has a significant better DFS than patients with constant HER2-zero (Log-rank P=0.037). In the HER2-low group, no significant differences in survival outcomes between constant HER2-low and HER2 low to zero (HR1.07, P=0.778). Conclusions: HER2 status showed instability from primary tumor to residual disease after neoadjuvant treatment. HER2 changes (zero to low) was associated with better DFS in HER-2 zero patients.

Prognostic Impact of CDKN2A Mutations Associated With Smoking and Drinking History in Japanese Digestive Cancers.

Organs of the digestive system are frequent sites of cancer development, and digestive tract cancers are the leading causes of death worldwide, including in Japan. Most of these cancers are associated with smoking or drinking habits. This study focused on the clinical and genomic characteristics of patients with these cancers using the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database, which comprises a large volume of data on Japanese patients who have undergone tumor profiling gene panel tests. The genomic and clinical data from patients with digestive tract cancers registered in C-CAT between 2019 and 2023 were retrospectively reviewed. The data were derived from 412 patients with esophageal squamous cell carcinoma, 558 with gastric adenocarcinoma, 3,368 with colorectal adenocarcinoma, 139 with hepatocellular carcinoma, 2,050 with cholangiocarcinoma, and 2,552 with pancreatic ductal adenocarcinoma. CDKN2A, CDKN2B, and MTAP mutations were associated with both smoking and drinking history, and patients with these mutations had a worse prognosis. Almost all gene alterations in CDKN2B and MTAP were deletions, often accompanied by CDKN2A deletion. CDKN2A mutation emerged as the most decisive prognostic factor among these mutations. Although CDKN2A mutations were frequently seen in esophageal squamous cell carcinoma, cholangiocarcinoma, and pancreatic ductal adenocarcinoma, statistically significant differences in survival outcomes were only identified in the latter two. CDKN2A mutations were associated with smoking and drinking in digestive cancers. This mutation was prevalent among patients with cholangiocarcinoma and pancreatic ductal adenocarcinoma, for whom they could serve as prognostic factors.

Establishment and validation of a predictive model for tracheotomy in critically ill patients and analysis of the impact of different tracheotomy timing on patient prognosis

BackgroundIn critically ill patients receiving invasive mechanical ventilation (IMV), it is unable to determine early which patients require tracheotomy and whether early tracheotomy is beneficial.MethodsClinical data of patients who were first admitted to the ICU and underwent invasive ventilation for more than 24 h in the Medical Information Marketplace in Intensive Care (MIMIC)-IV database were retrospectively collected. Patients were categorized into successful extubation and tracheotomy groups according to whether they were subsequently successfully extubated or underwent tracheotomy. The patients were randomly divided into model training set and validation set in a ratio of 7:3. Constructing predictive models and evaluating and validating the models. The tracheotomized patients were divided into the early tracheotomy group (< = 7 days) and the late tracheotomy group (> 7 days), and the prognosis of the two groups was analyzed.ResultsA total of 7 key variables were screened: Glasgow coma scale (GCS) score, pneumonia, traumatic intracerebral hemorrhage, hemorrhagic stroke, left and right pupil responses to light, and parenteral nutrition. The area under the receiver operator characteristic (ROC) curve of the prediction model constructed through these seven variables was 0.897 (95% CI: 0.876–0.919), and 0.896 (95% CI: 0.866–0.926) for the training and validation sets, respectively. Patients in the early tracheotomy group had a shorter length of hospital stay, IMV duration, and sedation duration compared to the late tracheotomy group (p < 0.05), but there was no statistically significant difference in survival outcomes between the two groups.ConclusionThe prediction model constructed and validated based on the MIMIC-IV database can accurately predict the outcome of tracheotomy in critically ill patients. Meanwhile, early tracheotomy in critically ill patients does not improve survival outcomes but has potential advantages in shortening the duration of hospitalization, IMV, and sedation.

Metabolic predictors of COVID-19 mortality and severity: a survival analysis.

The global healthcare burden of COVID-19 pandemic has been unprecedented with a high mortality. Metabolomics, a powerful technique, has been increasingly utilized to study the host response to infections and to understand the progression of multi-system disorders such as COVID-19. Analysis of the host metabolites in response to SARS-CoV-2 infection can provide a snapshot of the endogenous metabolic landscape of the host and its role in shaping the interaction with SARS-CoV-2. Disease severity and consequently the clinical outcomes may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. Hence, the host metabolome can help predict potential clinical risks and outcomes. In this prospective study, using a targeted metabolomics approach, we studied the metabolic signature in 154 COVID-19 patients (males=138, age range 48-69 yrs) and related it to disease severity and mortality. Blood plasma concentrations of metabolites were quantified through LC-MS using MxP Quant 500 kit, which has a coverage of 630 metabolites from 26 biochemical classes including distinct classes of lipids and small organic molecules. We then employed Kaplan-Meier survival analysis to investigate the correlation between various metabolic markers, disease severity and patient outcomes. A comparison of survival outcomes between individuals with high levels of various metabolites (amino acids, tryptophan, kynurenine, serotonin, creatine, SDMA, ADMA, 1-MH and carnitine palmitoyltransferase 1 and 2 enzymes) and those with low levels revealed statistically significant differences in survival outcomes. We further used four key metabolic markers (tryptophan, kynurenine, asymmetric dimethylarginine, and 1-Methylhistidine) to develop a COVID-19 mortality risk model through the application of multiple machine-learning methods. Metabolomics analysis revealed distinct metabolic signatures among different severity groups, reflecting discernible alterations in amino acid levels and perturbations in tryptophan metabolism. Notably, critical patients exhibited higher levels of short chain acylcarnitines, concomitant with higher concentrations of SDMA, ADMA, and 1-MH in severe cases and non-survivors. Conversely, levels of 3-methylhistidine were lower in this context.

Machine learning and multi-omics data reveal driver gene-based molecular subtypes in hepatocellular carcinoma for precision treatment.

The heterogeneity of Hepatocellular Carcinoma (HCC) poses a barrier to effective treatment. Stratifying highly heterogeneous HCC into molecular subtypes with similar features is crucial for personalized anti-tumor therapies. Although driver genes play pivotal roles in cancer progression, their potential in HCC subtyping has been largely overlooked. This study aims to utilize driver genes to construct HCC subtype models and unravel their molecular mechanisms. Utilizing a novel computational framework, we expanded the initially identified 96 driver genes to 1192 based on mutational aspects and an additional 233 considering driver dysregulation. These genes were subsequently employed as stratification markers for further analyses. A novel multi-omics subtype classification algorithm was developed, leveraging mutation and expression data of the identified stratification genes. This algorithm successfully categorized HCC into two distinct subtypes, CLASS A and CLASS B, demonstrating significant differences in survival outcomes. Integrating multi-omics and single-cell data unveiled substantial distinctions between these subtypes regarding transcriptomics, mutations, copy number variations, and epigenomics. Moreover, our prognostic model exhibited excellent predictive performance in training and external validation cohorts. Finally, a 10-gene classification model for these subtypes identified TTK as a promising therapeutic target with robust classification capabilities. This comprehensive study provides a novel perspective on HCC stratification, offering crucial insights for a deeper understanding of its pathogenesis and the development of promising treatment strategies.

Impact of neoadjuvant compared to adjuvant chemotherapy on prognosis in patients with hormone-receptor positive / HER2-negative breast cancer: A propensity score matching population-based study

BackgroundThe aim of this population-based cohort study was to investigate the impact of neoadjuvant chemotherapy (NACT) compared to adjuvant chemotherapy in prognosis among patients with HR+/HER2 negative breast cancer. MethodThis population-based study utilized data from the research database BCBaSe 3.0, based on the Swedish National Quality breast cancer register, including all patients with breast cancer diagnosis in Sweden between 2008 and 2019. Propensity score matching approach was applied. The outcomes of interest consisted of distant-disease free (DDFS), breast-cancer specific (BCSS), and overall survival (OS). ResultsIn total, 14 459 patients were included in the study cohort of whom 2086 received NACT. After 1:1 propensity score matching (PSM), 1539 patients in each study group were available for analyses. No statistically significant difference in survival outcomes were observed between patients treated with NACT compared to those treated with adjuvant chemotherapy (Hazard Ratio (HR) for DDFS: 1.20; 95 % CI: 0.80–1.79; HR for BCSS: 1.16; 95 % CI: 0.54–2.49; HR for OS: 1.14; 95 % CI: 0.64–2.05). ConclusionIn this population-based cohort study of patients with HR+/HER2-breast cancer, the use of NACT seems to be comparable to adjuvant chemotherapy in terms of prognosis, although non-inferiority cannot be proven by this study design. Until further evidence suggesting a survival benefit in favor of either treatment is available, NACT can be pursued when surgical-de-escalation is intended.

Abstract PO4-23-07: Impact of distance between tumor and nipple on locoregional recurrence in breast cancer

Abstract Introduction: Mastectomy is usually recommended for centrally located tumors due to the risk of nipple invasion. While it is well known that there is no significant difference in survival outcomes according to tumor location, central tumors have a higher likelihood of main lactiferous duct invasion, which can result in the migration of tumor cells to the periphery. Therefore, we conducted an investigation specifically focusing on locoregional recurrence (LRR) rates based on the tumor-to-nipple distance (TND). Method: We retrospectively collected the data of patients who underwent breast cancer surgery between 2004-2018 from two institutions. Patients who underwent neoadjuvant chemotherapy were excluded. TND information was obtained from preoperative MRI records. Results: A total of 9,014 patients were included in the study, and the median tumor-to-nipple distance (TND) was 3.4 (0.0-15.0) cm. For all patients, the restricted cubic spline curve analysis showed that the hazard risk of LRR increased with shorter TND. The pattern was more pronounced in the breast-conserving surgery (BCS) group, whereas the mastectomy group showed a relatively constant risk regardless of TND. Thus, we conducted survival analysis for 5,455 patients who underwent BCS. We set the cutoff for TND as 2.5cm as it showed the lowest p-value for LRR rate. Compared to those with TND &amp;gt;2.5cm, patients with TND≤2.5cm showed significantly lower LRR (HR,1.83;95%CI,[1.37-2.46],p&amp;lt; 0.001) and distant metastasis(DM) (HR,1.53;95%CI,[1.16-2.02],p=0.002) rates. Overall survival was not different between two groups (p=0.405). Cox-regression analysis revealed that TND still impacts LRR (HR,1.52;95%CI,[1.11-2.09],p=0.010) but not DM. Importantly, TND still remained significant factor affecting LRR when analyzed as continuous variable (HR,1.04; 95%CI,[1.02-1.06],p&amp;lt; 0.001). The prognostic impact of TND was particularly evident in patients with high mammographic density. Discussion: BCS can be performed for centrally located tumors, as it offers considerable oncologic safety compared to mastectomy. However, for patients who have a fear of recurrence and are reluctant to undergo re-operation, mastectomy would be a good choice. Citation Format: Jong-Ho Cheun, Eunhye Kang, Hong-Kyu Kim, Han-Byoel Lee, Hyeong-Gon Moon, Wonshik Han, Ki-Tae Hwang. Impact of distance between tumor and nipple on locoregional recurrence in breast cancer [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 PO4-23-07.

Abstract PS08-01: Antibody-Drug Conjugates (ADCs) in Breast Cancer: Real World Analysis of Outcomes

Abstract Methods: We estimated the distribution of progression-free survival (PFS), overall survival (OS), and time to treatment failure (TTF) using the Kaplan-Meier method. Differences in survival curves between groups categorized by initial ADC treatment and subsequent ADC treatments were assessed using the log-rank test. Cox proportional hazards regression models were employed to evaluate the association between each survival outcome and various measures of interest, such as age, gender, race, number of prior lines of treatment, hormone receptor status, and HER2 status. Results: The analysis included a total of 469 breast cancer patients, with the distribution of clinical characteristics summarized in Table 1. The median age at the start of ADC treatment was 50 years (range: 20-85). Among the patients, 263 patients (56%) received SC as their initial ADC treatment, while 44% received T-DXd. Additionally, 29 patients received both ADCs during metastatic treatment. The median follow-up time for all patients was 7.9 months (range: 0.1- 39.1). Out of the total patient population, 29% died, while 71% were still alive at the last follow-up. The median OS for all patients was 21.6 months. Median OS of patients receiving SC or T-DXd as their initial ADC treatment, was 14 and 37.1 months, respectively. Patients who received both SC and T-DXd had a median OS of 26.1 months. The median PFS for all patients was 6.0 months. Patients initially treated with SC had a median PFS of 4.7 months, whereas those treated with T-DXd had a median PFS of 9.0 months. In patients who received both, median of PFS was 4.9 months for T-DXd after SC, and 5.0 months for SC after T-DXd. The median TTF for all patients was 6.1 months. Patients initially treated with SC had a median TTF of 4.7 months, while those treated with T-DXd had a median TTF of 9.0 months. In patients who received T-DXd after SC, TTF was 4.9 months and SC after T-DXd was 5.0 months. Clinician-judged responses were seen in 180 (74%)of patients with SC only, 80 (41%) with T-DXd only, 9 (100%) with SC as 2nd ADC and 20 (100%) with T-DXd as 2nd ADC. Furthermore, the analysis explored the association of OS, PFS, and TTF with various measures of interest, including age, gender, race, number of prior lines of treatment, type of treatment, hormone receptor status, HER2 status, Ki67, and best response to ADC. Some notable associations were observed, such as ER-positive status being associated with marginally longer OS compared to ER-negative status (median 24.7 vs. 16.4 months; p=0.06), and HER2-positive status being associated with longer PFS compared to HER2-negative status (median 14.2 vs. 5.4 months; p&amp;lt; 0.001). However, these associations should be interpreted cautiously as they were obtained from univariate analysis. Conclusions: Overall, these results highlight the significant differences in survival outcomes between different ADC treatments in breast cancer patients, likely due to differing patient characteristics. Distribution of clinical characteristics across ADCs Citation Format: Akshara Singareeka Raghavendra, Zhongya Wang, Roland Bassett, Debu Tripathy. Antibody-Drug Conjugates (ADCs) in Breast Cancer: Real World Analysis of Outcomes [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 PS08-01.

Characteristics and significance of programmed cell death-related gene expression signature in skin cutaneous melanoma.

Programmed cell death (PCD) pathways play crucial roles in the pathogenesis of skin cutaneous melanoma (SKCM). Understanding their prognostic significance and clinical implications is imperative for the development of personalized treatment strategies. A total of 1466 PCD-related genes were analyzed using data from The Cancer Genome Atlas (TCGA)-SKCM cohort (n=353). Prognostic cell death index (CDI) was established and validated through survival analysis and predictive modeling. Functional enrichment, protein-protein interaction (PPI), consensus clustering, and tumor microenvironment assessment and drug sensitivity analysis were performed to elucidate the biological and clinical relevance of CDI. CDI effectively stratified SKCM patients into high and low-risk groups, demonstrating significant differences in survival outcomes. It exhibited predictive value for survival at 1, 3, and 5 years. The concordance index (C-index) was 0.794 in the training set, and 0.792 and 0.821 in the internal and external validation sets, respectively. The corresponding area under curve (AUC) was all above 0.75 in these data sets. Functional enrichment analysis revealed significant associations with immune response and inflammatory processes. PPI analysis identified key molecular modules associated with apoptosis and chemokine signaling. Consensus clustering unveiled three discernible subtypes demonstrating notable disparities in survival outcomes based on CDI expression profiles. Assessment of the tumor microenvironment highlighted correlations with immune cell infiltration such as M1 macrophages and T cells. Drug sensitivity analysis indicated tight correlations between CDI levels and response to immunotherapy. Our comprehensive analysis establishes the prognostic significance of PCD-related genes in SKCM. CDI emerges as a promising prognostic biomarker, offering insights into tumor biology and potential implications for personalized treatment strategies. Further validation and clinical integration of CDI are warranted to improve SKCM management and patient outcomes.

Mortality rates in Norwegian HEMS—a retrospective analysis from Central Norway

BackgroundHelicopter Emergency Medical Services (HEMS) provide rapid and specialized care to critically ill or injured patients. Norwegian HEMS in Central Norway serves an important role in pre-hospital emergency medical care. To grade the severity of patients, HEMS uses the National Advisory Committee for Aeronautics’ (NACA) severity score. The objective of this study was to describe the short- and long term mortality overall and in each NACA-group for patients transported by HEMS Trondheim using linkage of HEMS and hospital data.MethodsThe study used a retrospective cohort design, aligning with the STROBE recommendations. Patient data from Trondheim HEMS between 01.01.2017 and 31.12.2019 was linked to mortality data from a hospital database and analyzed. Kaplan Meier plots and cumulative mortality rates were calculated for each NACA group at day one, day 30, and one year and three years after the incident.ResultsTrondheim HEMS responded to 2224 alarms in the included time period, with 1431 patients meeting inclusion criteria for the study. Overall mortality rates at respective time points were 10.1% at day one, 13.4% at 30 days, 18.5% at one year, and 22.3% at three years. The one-year cumulative mortality rates for each NACA group were as follows: 0% for NACA 1 and 2, 2.9% for NACA 3, 10.1% for NACA 4, 24.7% for NACA 5 and 49.5% for NACA 6. Statistical analysis with a global log-rank test indicated a significant difference in survival outcomes among the groups (p < 2⋅10− 16).ConclusionAmong patients transported by Trondheim HEMS, we observed an incremental rise in mortality rates with increasing NACA scores. The study further suggests that a one-year follow-up may be sufficient for future investigations into HEMS outcomes.