Predictor Of Survival Research Articles

Clinician Prediction of Survival vs Calculated Prediction Scores in Patients Requiring Extracorporeal Membrane Oxygenation.

Determining appropriate extracorporeal membrane oxygenation (ECMO) candidacy ensures appropriate utilization of this costly resource. The current ECMO survival prediction scores do not consider clinician assessment of patient viability. This study compared clinician prediction of survival to hospital discharge versus prediction scores. The aim of this study was to compare clinician prediction of patients' survival to hospital discharge versus prognostic prediction scores (Respiratory ECMO Survival Prediction [RESP] or Survival After Veno-Arterial ECMO [SAVE] score) to actual survival. This was an observational descriptive study from January 2020 to November 2021 conducted with interviews of nurses, perfusionists, and physicians who were involved during the initiation of ECMO within the first 24 hours of cannulation. Data were retrieved from the medical record to determine prediction scores and survival outcomes at hospital discharge. Accuracy of clinician prediction of survival was compared to the RESP or SAVE prediction scores and actual survival to hospital discharge. Accurate prediction of survival to hospital discharge for veno-venous ECMO by nurses was 47%, 64% by perfusionists, 45% by physicians, and 45% by the RESP score. Accurate predictions of patients on veno-arterial ECMO were correct in 54% of nurses, 77% of physicians, and 14% by the SAVE score. Physicians were more accurate than the SAVE score, P = .021, and perfusionists were significantly more accurate than the RESP score, P = .044. There was no relationship between ECMO specialists' years of experience and accuracy of predications. Extracorporeal membrane oxygenation clinicians may have better predictions of survival to hospital discharge than the prediction scores. Further research is needed to develop accurate prediction tools to help determine ECMO eligibility.

Lymph node metastasis burden identifies head and neck squamous cell carcinoma patients benefiting from adjuvant chemoradiation: a propensity score-matching

IntroductionTo examine the influence of adjuvant chemoradiation therapy (CRT) on survival, stratified by varying numbers and level involved of metastatic lymph nodes in patients with head and neck squamous cell carcinoma (HNSCC). MethodsPatients who underwent surgery for metastatic, negative margin HNSCC without extranodal extension were retrospectively enrolled and divided into two groups based on adjuvant therapy received: radiotherapy (RT) and CRT. The impact of RT versus CRT, stratified by the number of positive lymph nodes and the level involved, on Disease-Free Survival (DFS) and Overall Survival (OS) was analyzed. ResultsFollowing propensity score matching, a total of 580 patients were included. The burden and level of lymph node metastasis were independent predictors of poorer survival. Among patients with no more than two positive lymph nodes or involvement of levels I-III, the addition of chemotherapy to RT did not demonstrate a significant improvement in prognosis. However, in patients with three or more positive lymph nodes, CRT showed improved DFS and OS compared to RT. In patients with involvement of levels IV-V, the addition of chemotherapy to RT resulted in a significant 24% reduction in the risk of recurrence and a 20% decrease in the risk of death. ConclusionIncorporation of adjuvant chemoradiation can lead to a favorable prognosis in patients with metastatic HNSCC. This impact was notable in cases where there were three or more positive lymph nodes or involvement of levels IV-V.

Ki67 is a better marker than PRAME in risk stratification of BAP1-positive and BAP1-loss uveal melanomas

BackgroundAccurate risk stratification of uveal melanoma (UM) patients is important for determining the interval and frequency of surveillance. Loss of BAP1 expression has been shown to be strongly associated with...

Development of a predictive algorithm for patient survival after traumatic injury using a five analyte blood panel.

Severe trauma can induce systemic inflammation but also immunosuppression, which makes understanding the immune response of trauma patients critical for therapeutic development and treatment approaches. By evaluating the levels of 59 proteins in the plasma of 50 healthy volunteers and 1000 trauma patients across five trauma centers in the United States, we identified 6 novel changes in immune proteins after traumatic injury and further new variations by sex, age, trauma type, comorbidities, and developed a new equation for prediction of patient survival. Blood was collected at the time of arrival at Level 1 trauma centers and patients were stratified based on trauma level, tissues injured, and injury types. Trauma patients had significantly upregulated proteins associated with immune activation (IL-23, MIP-5), immunosuppression (IL-10) and pleiotropic cytokines (IL-29, IL-6). A high ratio of IL-29 to IL-10 was identified as a new predictor of survival in less severe patients with ROC area of 0.933. Combining machine learning with statistical modeling we developed an equation ("VIPER") that could predict survival with ROC 0.966 in less severe patients and 0.8873 for all patients from a five analyte panel (IL-6, VEGF-A, IL-21, IL-29, and IL-10). Furthermore, we also identified three increased proteins (MIF, TRAIL, IL-29) and three decreased proteins (IL-7, TPO, IL-8) that were the most important in distinguishing a trauma blood profile. Biologic sex altered phenotype with IL-8 and MIF being lower in healthy women, but higher in female trauma patients when compared to male counterparts. This work identifies new responses to injury that may influence systemic immune dysfunction, serving as targets for therapeutics and immediate clinical benefit in identifying at-risk patients.

Notch ratio in pulmonary flow predicts long-term survival after pulmonary endarterectomy for chronic thromboembolic pulmonary hypertension.

Assessment of the pattern of the RV outflow tract Doppler provides insights into the hemodynamics of chronic thromboembolic pulmonary hypertension (CTEPH). We studied whether pre-operative assessment of timing of the pulmonary flow systolic notch by Doppler echocardiography is associated with long-term survival after pulmonary endarterectomy (PEA) for CTEPH. Fifty-nine out of 61 consecutive CETPH patients (mean age 53 ± 14 years, 34% male) whom underwent PEA between June 2002 and June 2005 were studied. Clinical, echocardiographic and hemodynamic variables were assessed pre-operatively and repeat echocardiography was performed 3 months after PEA. Notch ratio (NR) was assessed with pulsed Doppler and calculated as the time from onset of pulmonary flow until notch divided by the time from notch until end of pulmonary flow. Long-term follow-up was obtained between May 2021 and February 2022. Pre-operative mean pulmonary artery pressure (mPAP) was 45 ± 15 mmHg and pulmonary vascular resistance (PVR) was 646 ± 454 dynes.s.cm-5. Echocardiography before PEA showed that 7 patients had no notch, 33 had a NR < 1.0 and 19 had a NR > 1.0. Three months after PEA, echocardiography revealed a significant decrease in sPAP in long-term survivors with a NR < 1.0 and a NR > 1.0, while a significant increase in TAPSE/sPAP was only observed in the NR < 1.0 group. Mean long-term clinical follow-up was 14 ± 6 years. NR was significantly different between survivors and non-survivors (0.73 ± 0.25 vs. 1.1 ± 0.44, p < 0.001) but no significant differences were observed in mPAP or PVR. Long-term survival at 14 years was significantly better in patients with a NR < 1.0 compared to patients with a NR > 1.0 (83% vs. 37%, p = < 0.001). Pre-operative assessment of NR is a predictor of long-term survival in CTEPH patients undergoing PEA, with low mortality risk in patients with NR < 1.0. Long-term survivors with a NR < 1.0 and NR > 1.0 had a significant decrease in sPAP after PEA. However, the TAPSE/sPAP only significantly increased in the NR < 1.0 group. In the NR < 1.0 group, the 6-min walk test increased significantly between pre-operative and at 1-year post-operative follow-up. NR is a simple echocardiographic parameter that can be used in clinical decision-making for PEA.

Potential Survival Benefit of Upfront Surgery for Lung Tumors Unconfirmed but Highly Suspicious for Stage I Lung Cancer.

Patients with early-stage lung tumors that are highly suspicious for malignancy typically undergo a preoperative diagnostic workup, primarily through bronchoscopy or transthoracic biopsy. Those without a preoperative diagnosis may alternatively be treated with upfront surgery, contingent upon the potential for intraoperative diagnosis. Previous studies have yielded conflicting results regarding the impact of upfront surgery on the survival of these patients. Our study aimed to elucidate the effect of upfront surgery on the survival outcomes of patients undergoing surgery for early-stage lung cancer without a preoperative diagnosis. We analyzed the survival rate of 158 consecutive patients who underwent pulmonary resection for stage I lung cancer, either with or without a preoperative diagnosis. A total of 86 patients (54%) underwent upfront surgery. This approach positively impacted both disease-free survival (p=0.031) and overall survival (p=0.017). However, no significant differences were observed across subgroups based on sex, smoking status, forced expiratory volume in 1 second, histologic tumor size, or histologic subtype. Univariate analysis identified upfront surgery (p=0.020), age (p=0.002), maximum standardized uptake value (SUVmax) exceeding 7 (p=0.001), and histological tumor size greater than 20 mm (p=0.009) as independent predictors. However, multivariate analysis indicated that only SUVmax greater than 7 (p=0.011) was a significant predictor of unfavorable survival. Upfront surgery does not appear to confer a survival advantage in patients with stage I lung cancer undergoing surgical intervention.

Survival after Resection of Malignant Peripheral Nerve Sheath Tumors: introducing and validating a novel type-specific prognostic model

Abstract Background This study aimed to assess the performance of currently available risk calculators in a cohort of patients with malignant peripheral nerve sheath tumors (MPNST) and to create an MPNST-specific prognostic model including type-specific predictors for overall survival (OS). Methods This is a retrospective multicenter cohort study of patients with MPNST from eleven secondary or tertiary centers in The Netherlands, Italy and the USA. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000-2019 were included in this study. A multivariable Cox proportional hazard model for OS was estimated with pre-specified predictors (age, grade, size, NF-1 status, triton status, depth, tumor location and surgical margin). Model performance was assessed for the Sarculator and PERSARC calculators by examining discrimination (C-index) and calibration (calibration plots and observed-expected statistic; O/E-statistic). Internal-external cross-validation by different regions was performed to evaluate the generalizability of the model. Results A total of 507 patients with primary MPNSTs were included from 11 centers in 7 regions. During follow-up (median 8.7 years), 211 patients died. The C-index was 0.60 (95% CI 0.53-0.67) for both Sarculator and PERSARC. The MPNST-specific model had a pooled C-index of 0.69 (95%CI 0.65-0.73) at validation, with adequate discrimination and calibration across regions. Conclusions The MPNST-specific MONACO model can be used to predict 3-, 5-, and 10-year OS in patients with primary MPNST who underwent macroscopically complete surgical resection. Further validation may refine the model to inform patients and physicians on prognosis and support them in shared decision-making.

The effect of thoracic trauma scoring system in thoracic trauma patients with rib fracture

Objective Rib fractures are common in thoracic trauma patients. There are various factors, including flail chest, pulmonary contusion, and accompanying conditions, affecting morbidity and mortality. The study aimed to identify high-risk patients for morbidity and mortality with a scoring system that the authors created. Methods Cases over the age of 18 admitted due to trauma and diagnosed with rib fractures between 1 January 2019 and 1 March 2023, were included. Trauma scores were determined by applying the new trauma scoring system. Trauma scores and other variables regarding morbidity and mortality were evaluated. Results A total of 1023 cases were included in the study. The total trauma scores were higher in bilateral and multiple fractures. In those without respiratory failure, the total score was statistically significantly lower than in the groups with respiratory failure. The total score was significantly higher in those who needed surgery, those who were hospitalized, and those who needed intensive care compared to the non-surgical groups. However, there was no correlation between intensive care unit stay and total score. Trauma mechanism, presence of additional extrathoracic pathology, and thoracic trauma-age score were independent predictors of survival. Conclusion The present study demonstrated that the number of rib fractures and the presence of pulmonary contusion did not have an effect on mortality and morbidity. The presence of extrathoracic pathology and age significantly affect survival.

Exploring GZMK as a prognostic marker and predictor of immunotherapy response in breast cancer: unveiling novel insights into treatment outcomes

BackgroundGranzyme K (GZMK) is a crucial mediator released by immune cells to eliminate tumor cells, playing significant roles in inflammation and tumorigenesis. Despite its importance, the specific role of GZMK in breast cancer and its mechanisms are not well understood.MethodsWe utilized data from the TCGA and GEO databases and employed a range of analytical methods including GO, KEGG, GSEA, ssGSEA, and PPI to investigate the impact of GZMK on breast cancer. In vitro studies, including RT-qPCR, CCK-8 assay, cell cycle experiments, apoptosis assays, Celigo scratch assays, Transwell assays, and immunohistochemical methods, were conducted to validate the effects of GZMK on breast cancer cells. Additionally, Cox regression analysis integrating TCGA and our clinical data was used to develop an overall survival (OS) prediction model.ResultsAnalysis of clinical pathological features revealed significant correlations between GZMK expression and lymph node staging, differentiation grade, and molecular breast cancer subtypes. High GZMK expression was associated with improved OS, progression-free survival (PFS), and recurrence-free survival (RFS), as confirmed by multifactorial Cox regression analysis. Functional and pathway enrichment analyses of genes positively correlated with GZMK highlighted involvement in lymphocyte differentiation, T cell differentiation, and T cell receptor signaling pathways. A robust association between GZMK expression and T cell presence was noted in the breast cancer tumor microenvironment (TME), with strong correlations with ESTIMATEScore (Cor = 0.743, P < 0.001), ImmuneScore (Cor = 0.802, P < 0.001), and StromalScore (Cor = 0.516, P < 0.001). GZMK also showed significant correlations with immune checkpoint molecules, including CTLA4 (Cor = 0.856, P < 0.001), PD-1 (Cor = 0.82, P < 0.001), PD-L1 (Cor = 0.56, P < 0.001), CD48 (Cor = 0.75, P < 0.001), and CCR7 (Cor = 0.856, P < 0.001). Studies indicated that high GZMK expression enhances patient responsiveness to immunotherapy, with higher levels observed in responsive patients compared to non-responsive ones. In vitro experiments confirmed that GZMK promotes cell proliferation, cell division, apoptosis, cell migration, and invasiveness (P < 0.05).ConclusionOur study provides insights into the differential expression of GZMK in breast cancer and its potential mechanisms in breast cancer pathogenesis. Elevated GZMK expression is associated with improved OS and RFS, suggesting its potential as a prognostic marker for breast cancer survival and as a predictor of the efficacy of immunotherapy.

Does Metabolic Syndrome and Its Components Have Prognostic Significance for Renal and Cardiovascular Outcomes in IgA Nephropathy?

Patients with IgA nephropathy (IgAN), a chronic kidney disease (CKD), are significantly more likely to have cardiovascular (CV) mortality and morbidity than the general population. The occurrence of metabolic syndrome (MetS) and metabolic risk factors are independent risk factors for CV disease and renal progression. The purpose of this study was to determine how metabolic characteristics in a homogeneous population of CKD patients relate to prognosis. A total of 145 patients with CKD stages 1-4 diagnosed with IgA nephropathy (92 men and 53 women, aged 54.7 ± 13 years) were examined and monitored for a median of 190 months. All-cause mortality and any CV event, such as stroke, myocardial infarction, revascularization (CV), end-stage renal disease, and renal replacement therapy (renal), have been included in the composite endpoints (CV and renal). Patients with MetS had significantly more primary endpoint events (23/65 patients vs. 15/60 patients, p < 0.001) compared to the non-MetS group. The MetS group had a statistically significant increase in both primary renal and CV endpoints (18/65 vs. 10/60, p = 0.001), and in CV endpoint events (7/65 vs. 6/60, p = 0.029) among the secondary endpoints (CV and renal separately). Based on Cox regression analysis, the main endpoint independent predictors of survival were dyslipidemia, eGFR, hemoglobin, urine albuminuria, and diabetes mellitus. Independent predictors of secondary renal endpoints were dyslipidemia, hemoglobin, urine albumin, and eGFR. Predictors of secondary cardiovascular endpoints were gender, BMI, and diabetes. When Kaplan-Meier curves were analyzed at the combined endpoints (CV and renal) or each endpoint independently, significant differences were seen between MetS and non-MetS. With more MetS components, the primary endpoint rate increased significantly (MetS comp. 0 vs. MetS comp. 2+, primary endpoints, p = 0.012). Our results show that the metabolic profile has a prognostic role not only for renal endpoints but also for CV endpoints in IgAN. BMI, hyperuricemia, hypertension, and diabetes have a predictive value for the prognosis of IgA nephropathy.

A nomogram based on pretreatment radiomics and dosiomics features for predicting overall survival associated with esophageal squamous cell cancer

ObjectivesTo propose a nomogram-based survival prediction model for esophageal squamous cell carcinoma (ESCC) treated with definitive chemoradiotherapy using pretreatment computed tomography (CT), positron emission tomography (PET) radiomics and dosiomics features, and common clinical factors. MethodsRadiomics and dosiomics features were extracted from CT and PET images and dose distribution from 2 institutions. The least absolute shrinkage and selection operator (LASSO) with logistic regression was used to select radiomics and dosiomics features by calculating the radiomics and dosiomics scores (Rad-score and Dos-score), respectively, in the training model. The model was trained in 81 patients and validated in 35 patients at Center 1 using 10-fold cross validation. The model was externally tested in 26 patients at Center 2. The predictive clinical factors, Rad-score, and Dos-score were identified to develop a nomogram model. ResultsUsing LASSO Cox regression, 13, 11, and 19 CT, PET-based radiomics, and dosiomics features, respectively, were selected. The clinical factors T-stage, N-stage, and clinical stage were selected as significant prognostic factors by univariate Cox regression. In the external validation cohort, the C-index of the combined model of CT-based radiomics, PET-based radiomics, and dosiomics features with clinical factors were 0.74, 0.82, and 0.92, respectively. Significant differences in overall survival (OS) in the combined model of CT-based radiomics, PET-based radiomics, and dosiomics features with clinical factors were observed between the high- and low-risk groups (P = 0.019, 0.038, and 0.014, respectively). ConclusionThe dosiomics features have a better predicter for OS than CT- and PET-based radiomics features in ESCC treated with radiotherapy. Clinical relevance statementThe current study predicted the overall survival for esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy. The dosiomics features have a better predicter for overall survival than CT- and PET-based radiomics features.

Stratification of Homologous Recombination Deficiency-Negative High-Grade Ovarian Cancer by the Type of Peritoneal Spread into Two Groups with Distinct Survival Outcomes.

Homologous recombination deficiency (HRD) has evolved into a major diagnostic marker in high-grade ovarian cancer (HGOC), predicting the response to poly (adenosine diphosphate-ribose) polymerase inhibitors (PARPi) and also platinum-based therapy. In addition to HRD, the type of peritoneal tumor spread influences the treatment response and patient survival; miliary type tumor spread has a poorer predicted outcome than non-miliary type tumor spread. Known methods for HRD assessment were adapted for our technical requirements and the predictive-value integrated genomic instability score (PIGIS) for HRD assessment evolved as an outcome. PIGIS was validated in HGOC samples from 122 patients. We used PIGIS to analyze whether the type of tumor spread correlated with HRD status and whether this had an impact on survival. We demonstrated that PIGIS can discriminate HRD-positive from HRD-negative samples. Tumors with a miliary tumor spread are HRD-negative and have a very bad prognosis with a progression-free survival (PFS) of 15.6 months and an overall survival (OS) of 3.9 years. However, HRD-negative non-miliary spreading tumors in our cohort had a much better prognosis (PFS 35.4 months, OS 8.9 years); similar to HRD-positive tumors (PFS 34.7 months, OS 8.9 years). Our results indicate that in a predominantly PARPi naïve cohort, the type of tumor spread and concomitant cytoreduction efficiency is a better predictor of survival than HRD and that HRD may be an accidental surrogate marker for tumor spread and concomitant cytoreduction efficiency. It remains to be determined whether this also applies for sensitivity to PARPi.

PD-L1 expression as a potential predictor of immune checkpoint inhibitor efficacy and survival in patients with recurrent or metastatic nasopharyngeal cancer: a systematic review and meta-analysis of prospective trials.

The predictive value of programmed death-ligand 1 (PD-L1) expression in nasopharyngeal cancer (NPC) patients receiving immune checkpoint inhibitors (ICIs) remains controversial. This study aimed to evaluate the optimal threshold of PD-L1 expression in predicting the efficacy of ICIs in patients with recurrent or metastatic (R/M) NPC. A meta-analysis was performed by retrieving relevant literature from PubMed, EMBASE, and Cochrane Library databases. Data on the pooled risk ratio (RR), mean overall survival (OS), progression-free survival (PFS), overall response rate (ORR) with 95% confidence interval, and 1%, 10%, and 25% PD-L1 expression cutoff points were obtained to examine the role of PD-L1 as a biomarker in R/M NPC patients receiving immunotherapy. In total, 1,312 patients from 14 studies were included. An improvement in PFS was observed in both patients with PD-L1 ≥ 1% (RR = 0.76, 95% CI 0.62-0.92, P = 0.005) and those with PD-L1 < 1% (RR = 0.68, 95% CI: 0.35-1.32, P = 0.26) who received first-line treatment with immunotherapy, with no significant difference between these subgroups. The pooled ORR was significantly higher in patients with PD-L1 ≥ 1% (ORR = 0.37) than in those with PD-L1 < 1% (ORR = 0.22) (P < 0.01) undergoing subsequent-line treatment. However, when we used the PD-L1 cutoff values of 10% and 25%, there was no significant difference between the positive (PD-L1 expression ≥ the cutoff value) and negative (PD-L1 expression < the cutoff value) subgroups. PD-L1 ≥ 1% also tended to be associated with better PFS and OS. Our meta-analysis suggested that first-line immunotherapy could significantly improve PFS in R/M NPC patients, regardless of the PD-L1 expression levels. Positive PD-L1 expression (≥ 1%) might be a potential predictive biomarker for a better overall response to immunotherapy in R/M NPC patients in subsequent-line setting. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024495841 PROSPERO, identifier CRD42024495841.

DUX4 is a common driver of immune evasion and immunotherapy failure in metastatic cancers

Cancer immune evasion contributes to checkpoint immunotherapy failure in many patients with metastatic cancers. The embryonic transcription factor DUX4 was recently characterized as a suppressor of interferon-γ signaling and antigen presentation that is aberrantly expressed in a small subset of primary tumors. Here, we report that DUX4 expression is a common feature of metastatic tumors, with ~10–50% of advanced bladder, breast, kidney, prostate, and skin cancers expressing DUX4. DUX4 expression is significantly associated with immune cell exclusion and decreased objective response to PD-L1 blockade in a large cohort of urothelial carcinoma patients. DUX4 expression is a significant predictor of survival even after accounting for tumor mutational burden and other molecular and clinical features in this cohort, with DUX4 expression associated with a median reduction in survival of over 1 year. Our data motivate future attempts to develop DUX4 as a biomarker and therapeutic target for checkpoint immunotherapy resistance.

DUX4 is a common driver of immune evasion and immunotherapy failure in metastatic cancers.

Cancer immune evasion contributes to checkpoint immunotherapy failure in many patients with metastatic cancers. The embryonic transcription factor DUX4 was recently characterized as a suppressor of interferon-γ signaling and antigen presentation that is aberrantly expressed in a small subset of primary tumors. Here, we report that DUX4 expression is a common feature of metastatic tumors, with ~10-50% of advanced bladder, breast, kidney, prostate, and skin cancers expressing DUX4. DUX4 expression is significantly associated with immune cell exclusion and decreased objective response to PD-L1 blockade in a large cohort of urothelial carcinoma patients. DUX4 expression is a significant predictor of survival even after accounting for tumor mutational burden and other molecular and clinical features in this cohort, with DUX4 expression associated with a median reduction in survival of over 1 year. Our data motivate future attempts to develop DUX4 as a biomarker and therapeutic target for checkpoint immunotherapy resistance.

PET/CT based transformer model for multi-outcome prediction in oropharyngeal cancer

Background and purposeTo optimize our previously proposed TransRP, a model integrating CNN (convolutional neural network) and ViT (Vision Transformer) designed for recurrence-free survival prediction in oropharyngeal cancer and to extend its application to the prediction of multiple clinical outcomes, including locoregional control (LRC), Distant metastasis-free survival (DMFS) and overall survival (OS). Materials and MethodsData was collected from 400 patients (300 for training and 100 for testing) diagnosed with oropharyngeal squamous cell carcinoma (OPSCC) who underwent (chemo)radiotherapy at University Medical Center Groningen. Each patient’s data comprised pre-treatment PET/CT scans, clinical parameters, and clinical outcome endpoints, namely LRC, DMFS and OS. The prediction performance of TransRP was compared with CNNs when inputting image data only. Additionally, three distinct methods (m1-3) of incorporating clinical predictors into TransRP training and one method (m4) that uses TransRP prediction as one parameter in a clinical Cox model were compared. ResultsTransRP achieved higher test C-index values of 0.61, 0.84 and 0.70 than CNNs for LRC, DMFS and OS, respectively. Furthermore, when incorporating TransRP’s prediction into a clinical Cox model (m4), a higher C-index of 0.77 for OS was obtained. Compared with a clinical routine risk stratification model of OS, our model, using clinical variables, radiomics and TransRP prediction as predictors, achieved larger separations of survival curves between low, intermediate and high risk groups. ConclusionTransRP outperformed CNN models for all endpoints. Combining clinical data and TransRP prediction in a Cox model achieved better OS prediction.

Predictors of long-term survival in immune checkpoint inhibitor (ICI)-associated myocarditis.

e24026 Background: ICI-associated myocarditis carries a high morbidity and mortality, with close to half of patients experiencing major adverse cardiac events (MACE). Risk factors previously associated with short-term MACE include troponin T (TnT), neutrophil/lymphocyte ratio (NLR), and absolute lymphocyte count (ALC). In this study, we aimed to analyze the predictors of long-term survival. Methods: This single-center retrospective study included 37 patients diagnosed with ICI-associated myocarditis at Massachusetts General Hospital between March 2016 and March 2022. We collected demographics, diagnostic results, and myocarditis treatments from the electronic medical record. Patients were grouped by survival time: short-term ( &lt; 30 day), intermediate (30 to 360 day), or long-term ( &gt; 360 days) survival. We used chi-square and Kruskal-Wallis tests for descriptive statistics. Cut-off points of continuous variables were determined by ROC curve. Predictors of survival were analyzed by logistic regression models. Results: The cohort consisted of 29 males and 8 females with a median age of 75 years (IQR 68-79), and median follow-up of 5.6 months (IQR 0.5-14.9). The median time from ICI start to myocarditis onset was 50 days (IQR 36-91). Ten, 14, and 13 patients were in the short-term, intermediate, and long-term survival groups, respectively. By univariate analysis, predictors of long-term survival included initial NT-proBNP ≤ 450, NLR ≤ 4.44, ALC ≥ 1122, normal EKG QTc interval (≤ 450 ms in male or ≤ 460 ms in female), and TnT decrement ≥ 42% by day 8 of immunosuppression (Table 1). All patients with long-term survival presented with a normal left ventricular ejection fraction (LVEF ≥ 55%), which made it uninterpretable using logistic regression models. Normal LVEF was significantly associated with long-term survival by using chi-square test (p = 0.002). While TnT elevation &gt; 75x the upper limit of normal (ULN) was strongly associated with short-term survival (p = 0.001), it was not associated with long-term survival (p = 0.23). The use of second-line immunosuppression in addition to corticosteroids did not have a significant impact on long-term survival (p = 0.69). Conclusions: NLR, ALC, NT-proBNP, QTc interval, and a substantial decrease in TnT at day 8 after immunosuppression are all associated with long-term survival in ICI myocarditis. [Table: see text]

Racial disparities in presentation and survival for lobular breast cancer.

1596 Background: We characterized differences in presentation and survival, and identified predictors of survival, among women of varying race with lobular breast cancer. We also assessed if these trends were unique to ILC by comparing with invasive ductal carcinoma (IDC) and mixed invasive ductal-lobular carcinoma (IDLC). Methods: Using the SEER database, we performed a population-based retrospective cohort study of women diagnosed with ILC, IDC, and IDLC between 1998 and 2019. We collected race, age, marital status, and income. Clinical data included grade, size, laterality, clinical stage, receptor status, surgery type, chemotherapy, radiation, and breast-cancer-specific survival (BCSS). Differences between racial groups were assessed using Chi-square tests or one-way ANOVA. To identify predictors of survival, Cox-proportional hazard models were constructed. Statistical analyses were performed using SAS and P values &lt; 0.05 were considered significant. Results: 38,769 women with ILC were identified, including 32,857 White, 2398 Black, 2352 Asian, and 1162 women of other race. Black women presented with higher-grade, advanced clinical stage, ER+ disease, N2-3 stage, and lower rates of unilateral/bilateral mastectomy than White women. Black women were more likely to not undergo surgery (7.13%), compared with White (4.25%) and Asian (4.04%) women ( P = .0001). Asian women were younger, had more ER-/PR- ILC, and received more chemotherapy. The five-year BCSS rates in Black, White, Asian, and women of other race were 91.5%, 94.2%, 93.7%, and 95.7%, respectively ( P&lt; .0001). Predictors of worse survival include Black race (HR 1.32, P &lt; .0001), ER-/PR- (HR 2.18, P&lt; .0001), ER+/PR- (HR 1.52, P&lt; .0001), and no surgery (HR 4.19, P &lt; .0001). Radiotherapy was associated with improved survival (HR 0.82, P &lt; .0001), while chemotherapy did not affect survival (HR 1.1, P= 0.0504). In comparing across breast cancer subtypes, Black women similarly present with higher grade tumors, advanced clinical stage, ER+ disease, and had higher rates of surgery omission in IDC and IDLC. However, ER-/PR- subtype was notably higher in ILC among Asian women compared with IDC, whereas Black women have higher rates of ER+/PR+ and ER-/PR- ILC. Black women had the lowest five-year BCSS rates across all breast cancer subtypes. Predictors of worse survival in IDC and IDLC include Black race and negative hormone receptor status, while radiation therapy was associated with improved survival. Conclusions: There are differences in clinical presentation of invasive lobular breast cancer according to race.Black women had more advanced disease, while Asian women were younger. Across all subtypes, overall survival for Black women at 5 years was worse compared to other racial groups. Our data provides insight into the complex interactions of race, clinical characteristics, and survival outcomes in lobular breast cancer, with implications for screening considerations.

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.

Asymmetric Dimethylarginine and NT-proBNP Levels Provide SynergisticInformation in PulmonaryArterial Hypertension.

Plasma asymmetric dimethylarginine (ADMA) is elevated in pulmonary arterial hypertension (PAH) and is associated with unfavorable outcomes. The aim of this study was to assess changes in ADMA plasma levels for monitoring disease progression and outcomes during PAH-specific therapy. ADMA was measured at baseline and after at least 6months of follow-up using enzyme-linked immunosorbent assay and high-performance liquid chromatography. Changes in ADMA were analyzed in relation to changes in established PAH markers, including hemodynamic status, N-terminal pro-brain natriuretic peptide (NT-proBNP) and risk assessment scores. Impact on survival was assessed using Kaplan-Meier curves and Cox proportional hazards models. Between 2008 and 2019, ADMA samples were collected prospectively from 215 patients with PAH. Change in ADMA plasma level was a predictor of disease progression and survival. ΔADMA (median-0.03μmol/L; 95%CI:-0.145 to 0.0135) was correlated with change in mean pulmonary arterial pressure (P< 0.005; rS=0.287) but was not significantly correlated with ΔNT-proBNP (P=0.056; rS=0.135). Patients with decreased ADMA plasma levels at follow-up had better 3-year and 5-year survival rates (88% and 80%, respectively, vs 72% and 53% in those without decreases in ADMA) (P< 0.005; pulmonary hypertension-related mortality or lung transplantation). Patients with decreases in both ADMA and NT-proBNP had better survival rates compared with patients in whom only 1 parameter improved (P< 0.005). ΔADMA was a significant predictor of survival in Cox regression analysis and also when corrected for ΔNT-proBNP (HRs: 1.27 and 1.35, respectively; P< 0.005). ADMA and NT-proBNP provide synergistic prognostic information for patients with PAH. ADMA could be used as an objective and distinct biomarker for monitoring treatment response in PAH.