Predictor Of Long-term Survival Research Articles

Renal remission status and long-term renal survival in lupus nephritis patients

Aim of the workTo compare long-term renal survival in lupus nephritis (LN) patients who achieved complete (CR), partial (PR), or no remission following LN induction therapy. Patients and methodsEligible patients with biopsy-proven LN were categorized into ordinal (CR, PR, or no remission) or binary (remission or no remission) at 6, 12, 24, 36 months post diagnosis according to modified Aspreva Lupus Management Study (mALMS) criteria. The primary endpoint was long-term renal survival. ResultsThe study included 161 patients with LN, with a mean age 36.3 ± 8.2 years, age at biopsy 26.2 ± 7.4 years; 146 females and 15 males (F:M 9.3:1). All patients received induction therapy 6 months before or after biopsy with follow up duration ≥3 years. 114 (70.8 %) patients achieved long term survival, while 47 (29.2 %) ended up with end-stage renal disease (ESRD). Those with CR were more likely to have long-term survival (p < 0.001). A significant relation was found between maintenance therapies at different time points in those receiving azathioprine (AZA) (p = 0.002, p = 0.011, p = 0.016 and p = 0.003 respectively), as well as hydroxychloroquine (HCQ) (p < 0.003, p < 0.001, p = 0.011, p < 0.001 and p < 0.001 respectively) with long term survival. Cardiovascular and neuropsychiatric manifestations were significantly associated with ESRD/mortality (p = 0.003 and p = 0.002 respectively). The most significant predictor of long-term survival was complete remission at 6 months (β-3.745, p = 0.025). ConclusionIn LN, renal remission was significantly associated with long term renal survival. Receiving AZA and HCQ have a significant association and CR at 6 months was the best predictor for long-term survival in LN patients.

Predictive utility of nomogram based on serum glucose-regulated protein 78 and kidney function for long-term kidney graft survival

The estimated glomerular filtration rate (eGFR) at 1 year post-transplantation is a well-established predictor of long-term graft survival; however, its predictive accuracy needs improvement. We retrospectively analyzed data from 51 kidney transplant recipients at Kanazawa Medical University Hospital (January 2001–February 2015). Cox regression was used to identify risk factors for death-censored graft loss and create a nomogram to predict graft survival at 15 years post-transplantation. The predictive factors ultimately included in the nomogram included eGFR and serum glucose-regulated protein 78 (GRP78) at 1 year post-transplantation. In terms of discrimination, assessed by area under the receiver operating characteristic curve (AUC-ROC), no significant difference was noted between the eGFR model (AUC 0.84 [0.67–1.00]) and nomogram (AUC 0.92 [0.82–1.00]) (p = 0.38). However, calibration, evaluated by the calibration plot, indicated superiority of the nomogram over the eGFR model, confirmed in the internal validation cohort using the Bootstrap method. Regarding clinical value evaluated by decision curve analysis, the nomogram showed a greater net benefit than the eGFR model, especially at wider diagnostic thresholds (particularly important lower thresholds). Our findings suggest the added predictive value of serum GRP78 at 1 year post-transplantation for long-term graft survival prediction.

Which Scoring System Best Predicts Long-term Survival in Patients with Spinal Metastasis in the Era of Targeted Systemic Treatment? A Comparative Study of Eight Prognostic Models.

Retrospective observational study. To evaluate the accuracy of eight scoring systems, including the Tomita, modified Tokuhashi, modified Bauer, Rades, Oswestry Spinal Risk index (OSRI), Lei, New England Spinal Metastasis Score, and Skeletal Oncology Research Group (SORG) nomogram, for predicting long-term survival of patients with spinal metastasis. Predicting the prognosis of spinal metastasis is vital for surgical decisions, yet the effectiveness of existing scoring systems in identifying long-term survival remains unclear. 456 cases were finally included. Prognostic scores were compared with survival outcomes. Receiver operating characteristic (ROC) curves were analyzed for the entire cohort and across three distinct time periods to evaluate the area under the curve (AUC) for 1-year and 2-year survival, alongside Harrell's C-statistic. The mean patient age was 58.9 years, and the median survival time was 8.6 months. For the entire cohort, the SORG nomogram, OSRI, and modified Tokuhashi scores yielded Harrell's C-index values of 0.64, 0.63, and 0.62, respectively. For 1-year survival prediction, the SORG nomogram, OSRI, and modified Tokuhashi score demonstrated moderate discriminative power, with AUC values of 0.72, 0.71, and 0.70, respectively. Similarly, for 2-year survival prediction, the modified Tokuhashi score, SORG nomogram, and OSRI also revealed moderate discriminative power, with AUC values of 0.73, 0.72, and 0.70, respectively. For patients who underwent surgery in the most recent period, OSRI demonstrated the highest predictive accuracy for 1-year survival, with a Harrell's C-index of 0.63 and an AUC of 0.68, and 2-year survival, with a Harrell's C-index of 0.63 and an AUC of 0.64. Most scoring systems exhibited low discriminative power, with only the SORG nomogram, OSRI, and modified Tokuhashi scores demonstrating moderate power for predicting long-term survival. In the most recent period, the OSRI demonstrated the highest predictive accuracy for both 1-year and 2-year survival.

Vegetation Length is Associated with Long-term Survival in Patients Treated Surgically for Infective Endocarditis.

The impact of vegetation length on therapeutic decision-making and prediction of long-term survival of patients with infective endocarditis is a highly topical issue. The aim of the study was to clarify the impact of vegetation length greater than 10 mm on long-term survival treated surgically for infective endocarditis. Patients treated surgically for infective endocarditis in our hospital from January 2006 to November 2022 and were successfully followed up were included in the retrospective analysis. 814 survivors discharged from our medical center were successfully followed up to the date of death or the end date of the research and allocated to a group with vegetation length <10 mm (n = 432) or ≥10 mm (n = 382). The average follow-up time was 75.1 ± 1.8 months. Multivariate analysis indicated vegetation length ≥10 mm was associated with 1-year and 5-year mortality. Multivariate analysis of Cox regression identified vegetation length ≥10 mm to be associated with all-time mortality. Multivariate analysis identified male gender, long time between symptoms and surgery, more preoperative left ventricular ejection fraction (LVEF) and more preoperative aortic regurgitation to be associated with vegetation length ≥10 mm in infective endocarditis. Our study indicated that vegetation length ≥10 mm was associated with long-term survival in patients treated surgically for infective endocarditis.

A study predicting long-term survival capacity in postoperative advanced gastric cancer patients based on MAOA and subcutaneous muscle fat characteristics

BackgroundThe prognosis of advanced gastric cancer (AGC) is relatively poor, and long-term survival depends on timely intervention. Currently, predicting survival rates remains a hot topic. The application of radiomics and immunohistochemistry-related techniques in cancer research is increasingly widespread. However, their integration for predicting long-term survival in AGC patients has not been fully explored.MethodsWe Collected 150 patients diagnosed with AGC at the Affiliated Zhongshan Hospital of Dalian University who underwent radical surgery between 2015 and 2019. Following strict inclusion and exclusion criteria, 90 patients were included in the analysis. We Collected postoperative pathological specimens from enrolled patients, analyzed the expression levels of MAOA using immunohistochemical techniques, and quantified these levels as the MAOAHScore. Obtained plain abdominal CT images from patients, delineated the region of interest at the L3 vertebral body level, and extracted radiomics features. Lasso Cox regression was used to select significant features to establish a radionics risk score, convert it into a categorical variable named risk, and use Cox regression to identify independent predictive factors for constructing a clinical prediction model. ROC, DCA, and calibration curves validated the model’s performance.ResultsThe enrolled patients had an average age of 65.71 years, including 70 males and 20 females. Multivariate Cox regression analysis revealed that risk (P = 0.001, HR = 3.303), MAOAHScore (P = 0.043, HR = 2.055), and TNM stage (P = 0.047, HR = 2.273) emerged as independent prognostic risk factors for 3-year overall survival (OS) and The Similar results were found in the analysis of 3-year disease-specific survival (DSS). The nomogram developed could predict 3-year OS and DSS rates, with areas under the ROC curve (AUCs) of 0.81 and 0.797, respectively. Joint calibration and decision curve analyses (DCA) confirmed the nomogram’s good predictive performance and clinical utility.ConclusionIntegrating immunohistochemistry and muscle fat features provides a more accurate prediction of long-term survival in gastric cancer patients. This study offers new perspectives and methods for a deeper understanding of survival prediction in AGC.

Clinical features and prediction of long-term survival after surgery for perihilar cholangiocarcinoma.

The treatment of perihilar Cholangiocarcinoma (pCCA) poses specific challenges not only due to its high perioperative complication rates but also due its dismal long-term prognosis with only a few long-term survivors (LTS) among the patients. Therefore, in this analysis characteristics and predictors of LTS in pCCA patients are investigated. In this single center analysis, patients undergoing curative-intent liver resection for pCCA between 2010 and 2022 were categorized into long-term and short-term survivors (STS) excluding perioperative mortality. Binary logistic regression was used to determine key differences between the groups and to develop a prognostic composite variable. This composite variable was subsequently tested in the whole cohort of surgically treated pCCA patients using Cox Regression analysis for cancer-specific survival (CSS). Within a cohort of 209 individuals, 27 patients were identified as LTS (median CSS = 125 months) and 55 patients as STS (median CSS = 16 months). Multivariable analysis identified preoperative portal vein infiltration (OR = 5.85, p = 0.018) and intraoperative packed red blood cell (PRBC) transfusions (OR = 10.29, p = 0.002) as key differences between the groups. A prognostic composite variable based on these two features was created and transferred into a Cox regression model of the whole cohort. Here, the composite variable (HR = 0.35, p<0.001), lymph node metastases (HR = 2.15, p = 0.001) and postoperative complications (HR = 3.06, p<0.001) were identified as independent predictors of CSS. Long-term survival after surgery for pCCA is possible and is strongly negatively associated with preoperative portal vein infiltration and intraoperative PRBC transfusion. As these variables are part of preoperative staging or can be modulated by intraoperative technique, the proposed prognostic composite variable can easily be transferred into clinical management to predict the oncological outcome of patients undergoing surgery for pCCA.

Temporal trends and prognostic impact of reperfusion modalities in Tunisian patients presenting with ST-elevation myocardial infarction: A 20-year analysis.

With the advent of reperfusion therapies, management of patients presenting with ST-elevation myocardial infarction (STEMI) has witnessed significant changes during the last decades. We sought to analyze temporal trends in reperfusion modalities and their prognostic impact over a 20-year period in patients presenting with STEMI the Monastir region (Tunisia). Patients from Monastir region presenting for STEMI were included in a 20-year (1998-2017) single center registry. Reperfusion modalities, early and long-term outcomes were studied according to five four-year periods. Out of 1734 patients with STEMI, 1370 (79%) were male and mean age was 60.3 ± 12.7 years. From 1998 to 2017, primary percutaneous coronary intervention (PCI) use significantly increased from 12.5% to 48.3% while fibrinolysis use significantly decreased from 47.6% to 31.7% (p<0.001 for both). Reperfusion delays for either fibrinolysis or primary PCI significantly decreased during the study period. In-hospital mortality significantly decreased from 13.7% during Period 1 (1998-2001) to 5.4% during Period 5 (2014-2017), (p=0.03). Long-term mortality rate (mean follow-up 49.4 ± 30.7 months) significantly decreased from 25.3% to 13% (p<0.001). In multivariate analysis, age, female gender, anemia on-presentation, akinesia/dyskinesia of the infarcted area and use of plain old balloon angioplasty were independent predictors of death at long-term follow-up whereas primary PCI use and preinfaction angina were predictors of long-term survival. In this long-term follow-up study of Tunisian patients presenting for STEMI, reperfusion delays decreased concomitantly to an increase in primary PCI use. In-hospital and long-term mortality rates significantly decreased from 1998 to 2017.

Long-Term Follow-Up of Patients with Advanced Colorectal Liver Metastasis: A Survival Analysis from the Randomized Controlled Multicenter Trial LIGRO.

The objective of this study was to evaluate the long-term oncological outcomes of patients with colorectal liver metastasis (CRLM) randomized for associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) or 2-stage hepatectomy (TSH). For advanced CRLM, TSH or ALPPS may be needed for tumor freedom. The randomized, controlled, multicenter trial LIGRO showed an increased resection rate in patients who underwent ALPPS but no difference in morbidity or mortality. The 2-year survival analysis revealed better overall survival in the ALPPS group. Here, the long-term survival analysis from the LIGRO trial is reported. In the LIGRO trial, 100 patients were randomized to TSH or ALPPS, with the option of rescue ALPPS if insufficient growth was found after the initial step of TSH. Patients were enrolled between June 2014 and August 2016. Follow-up data for this study were collected between November 2022 and February 2023. In total, 16 patients were alive at the end of the follow-up period. The estimated median follow-up time was 93 months. Estimated median overall survival times were 45 months in the ALPPS group and 27 months in the TSH group (P = 0.057), with 5-year survival rates of 31% and 20%, respectively. Positive prognostic factors were liver tumor-free status at the first follow-up and rectal primary tumor. Negative prognostic factors were extrahepatic disease and increasing CLRM size. Liver tumor-free status is a predictor of long-term survival, along with extrahepatic disease, large CRLM size, and rectal primary tumor. Survival did not significantly differ between patients treated with ALPPS or TSH.

Preoperative Prediction of Long-Term Survival After Surgery in Patients with Resectable Pancreatic Ductal Adenocarcinoma

BackgroundAlthough some clinical trials have demonstrated the benefits of neoadjuvant therapy for resectable pancreatic ductal adenocarcinoma (PDAC), its optimal candidate has not been clarified. This study aimed to detect predictive prognostic factors for resectable PDAC patients who underwent upfront surgery and identify patient cohorts with long-term survival without neoadjuvant therapy.Patients and MethodsA total of 232 patients with resectable PDAC who underwent upfront surgery between January 2008 and December 2019 were evaluated.ResultsThe median overall survival (OS) time and 5-year OS rate of resectable PDAC with upfront surgery was 31.5 months and 33.3%, respectively. Multivariate analyses identified tumor diameter in computed tomography (CT) ≤ 19 mm [hazard ratio (HR) 0.40, p < 0.001], span-1 within the normal range (HR 0.54, p = 0.023), prognostic nutritional index (PNI) ≥ 44.31 (HR 0.51, p < 0.001), and lymphocyte-to-monocyte ratio (LMR) ≥ 3.79 (HR 0.51, p < 0.001) as prognostic factors that influence favorable prognoses after upfront surgery. According to the prognostic prediction model based on these four factors, patients with four favorable prognostic factors had a better prognosis with a 5-year OS rate of 82.4% compared to others (p < 0.001). These patients had a high R0 resection rate and a low frequency of tumor recurrence after upfront surgery.ConclusionsWe identified patients with long-term survival after upfront surgery by prognostic prediction model consisting of tumor diameter in CT, span-1, PNI, and LMR. Evaluation of anatomical, biological, nutritional, and inflammatory factors may be valuable to introduce an optimal treatment strategy for resectable PDAC.

Predictors of long-term survival after resection of adenocarcinoma arising from intraductal papillary mucinous neoplasm and derivation of a prognostic model: An international multicenter study (ADENO-IPMN study)

Predictors of long-term survival after resection of adenocarcinoma arising from intraductal papillary mucinous neoplasms are unknown. This study determines predictors of long-term (>5 years) disease-free survival and recurrence in adenocarcinoma arising from intraductal papillary mucinous neoplasms and derives a prognostic model for disease-free survival. Consecutive patients who underwent pancreatic resection for adenocarcinoma arising from intraductal papillary mucinous neoplasms in 18 academic pancreatic centers in Europe and Asia between 2010 to 2017 with at least 5-year follow-up were identified. Factors associated with disease-free survival were determined using Cox proportional hazards model. Internal validation was performed, and discrimination and calibration indices were assessed. In the study, 288 patients (median age, 70 years; 52% male) were identified; 140 (48%) patients developed recurrence after a median follow-up of 98 months (interquartile range, 78.4-123), 57 patients (19.8%) developed locoregional recurrence, and 109 patients (37.8%) systemic recurrence. At 5 years after resection, the overall and disease-free survival was 46.5% (134/288) and 35.0% (101/288), respectively. On Cox proportional hazards model analysis, multivisceral resection (hazard ratio, 2.20; 95% confidence interval, 1.06-4.60), pancreatic tail location (hazard ratio, 2.34; 95% confidence interval, 1.22-4.50), poor tumor differentiation (hazard ratio, 2.48; 95% confidence interval, 1.10-5.30), lymphovascular invasion (hazard ratio, 1.74; 95% confidence interval, 1.06-2.88), and perineural invasion (hazard ratio, 1.83; 95% confidence interval, 1.09-3.10) were negatively associated with long-term disease-free survival. The final predictive model incorporated 8 predictors and demonstrated good predictive ability for disease-free survival (C-index, 0.74; calibration, slope 1.00). A third of patients achieve long-term disease-free survival (>5 years) after pancreatic resection for adenocarcinoma arising from intraductal papillary mucinous neoplasms. The predictive model developed in the current study can be used to estimate the probability of long-term disease-free survival.

MSR49 Long-Term Survival Prediction in Early Breast Cancer: A Machine Learning Approach With Random Survival Forest

MSR49 Long-Term Survival Prediction in Early Breast Cancer: A Machine Learning Approach With Random Survival Forest

Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypes

Breast cancer (BC) is a leading cause of cancer-related death worldwide. The diverse nature and heterogeneous biology of BC pose challenges for survival prediction, as patients with similar diagnoses often respond differently to treatment. Clinically relevant BC intrinsic subtypes have been established through gene expression profiling and are implemented in the clinic. While these intrinsic subtypes show a significant association with clinical outcomes, their long-term survival prediction beyond 5 years often deviates from expected clinical outcomes. This study aimed to identify naturally occurring long-term prognostic subgroups of BC based on an integrated multi-omics analysis. This study incorporates a clinical cohort of 335 untreated BC patients from the Oslo2 study with long-term follow-up (>12 years). Multi-Omics Factor Analysis (MOFA+) was employed to integrate transcriptomic, proteomic, and metabolomic data obtained from the tumor tissues. Our analysis revealed three prominent multi-omics clusters of BC patients with significantly different long-term prognoses (p = 0.005). The multi-omics clusters were validated in two independent large cohorts, METABRIC and TCGA. Importantly, a lack of prognostic association to long-term follow-up above 12 years in the previously established intrinsic subtypes was shown for these cohorts. Through a systems-biology approach, we identified varying enrichment levels of cell-cycle and immune-related pathways among the prognostic clusters. Integrated multi-omics analysis of BC revealed three distinct clusters with unique clinical and biological characteristics. Notably, these multi-omics clusters displayed robust associations with long-term survival, outperforming the established intrinsic subtypes.

The role of CT-assessed sarcopenia and visceral adipose tissue in predicting long-term survival in patients undergoing elective endovascular infrarenal aortic repair.

To evaluate if ileo-psoas muscle size and visceral adipose tissue (VAT) can predict long-term survival after endovascular aneurysm repair (EVAR). Patients who underwent EVAR between 2004 and 2012 in a single centre were included. Total psoas muscle area (TPA), abdominal VAT area, subcutaneous adipose tissue (SAT), and total adipose tissue were measured on the preoperative CT. Primary endpoint was all-cause mortality. Values are presented as median and interquartile range or absolute number and percentage. Cox regression analyses were performed to assess the associations with mortality. Two hundred and eighty-four patients could be included in the study. During a median follow-up of 8 (4-11) years, 223 (79.9%) patients died. Age (P ≤ .001), cardiovascular (P = .041), cerebrovascular (P = .009), renal diseases (P = .002), and chronic obstructive pulmonary disease (P ≤ .001) were independently associated with mortality. TPA was associated with mortality in a univariate (P = .040), but not in a multivariate regression model (P = .764). No significant association was found between mortality and TPA index (P = .103) or any of the adiposity measurements with the exception of SAT (P = .040). However, SAT area loss in a multivariate analysis (P = .875). Assessment of core muscle size and VAT did not contribute to improving the prediction of long-term survival after EVAR. The finding of this study contradicts the previously claimed utility of core muscle size and VAT in predicting long-term survival after EVAR.

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

BackgroundAssessment 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.MethodsFifty-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.ResultsPre-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).ConclusionPre-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.

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]

Intermediate and long-term survival prediction using prognostic scores in patients undergoing salvage TIPS for uncontrolled variceal bleeding

Intermediate and long-term survival prediction using prognostic scores in patients undergoing salvage TIPS for uncontrolled variceal bleeding

Systemic inflammation-modified PG-SGA index in the survival prediction of advanced cancers.

12056 Background: The tight association between inflammation and nutrition has been established. Whether the systemic inflammatory indicators could increase the predictive power of nutrition assessment tools in the survival of advanced cancers remains unclear. Methods: In this retrospective study, advanced cancer patients were enrolled from the West China Hospital between Nov 2019 and Sep 2023. Five systemic inflammatory indicators were selected including the systemic inflammatory index (SII), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and advanced lung cancer inflammation index (ALI). Nutritional status was evaluated by the PG-SGA. Kaplan-Meier curves, restricted cubic splines (RCS), and Cox regression analyses were used to estimate the effects of systemic inflammation indices as well as systemic inflammation-modified PG-SGA index on the survival of cancer patients. Stratified and sensitive analyses were conducted to determine the high-risk subgroups and check the robustness of the main findings. Results: In total, there were 1,065 advanced-stage cancer patients included in this study, with a mean age of 58.18 years old. Advanced lung cancer (265 cases, 24.9%) accounted for relatively higher proportions of the whole study population, followed by colorectal cancer (167 cases, 15.7%), esophagus cancer (143 cases, 13.4%), and gastric cancer (139 cases, 13.0%). With a median follow-up of 1,300 days, 501 deaths (47.04%) were observed. Multivariate Cox regression analysis showed that ALI maintained the best predictive power in predicting the all-cause mortality of advanced-stage cancer patients when compared with other systemic inflammation indicators (4th quartile: hazard ratio (HR)= 0.38, 95% confidence interval (CI): 0.29, 0.50, P&lt;0.001), with a C-index of 0.615. The novel inflammation-modified PG-SGA/ALI index showed better predictive value in identifying the high-risk subgroups of advanced-stage cancer patients, with an AUC of ROC of 0.68 in 365-day mortality, 0.65 in 730-day mortality, and 0.64 in 1300-day survival prediction, respectively. The C-index (0.626), calibration curves, and decision curve analysis validated the promising predictive accuracy of the PG-SGA/ALI index in predicting the all-cause mortality of advanced-stage cancer patients. No significant interaction was observed between subgroups. A series of sensitive analyses supported the consistent findings as we determined in the main regression. Conclusions: Our study highlights that the PG-SGA/ALI index has superior predictive value than original PG-SGA criteria in short- and long-term survival prediction of advanced cancers. The PG-SGA/ALI index would be a more accurate tool for nutritional evaluation and prognosis prediction among cancer patients during clinical practice.

Identifying and Validating an Angiogenesis-related Signature for the Prognosis of Head and Neck Squamous Cell Carcinoma.

The present study aimed todevelop a prognostic model for HNSCC treatment on the basis of angiogenesis-related signatures. Head and Neck Squamous Cell Carcinoma (HNSCC) is the most frequent malignancy with poor prognostic outcomes in the head and neck. Angiogenesis plays a critical role in tumorigenesis and is expected to be an effective therapeutic target. The RNA-seq dataset TCGA-HNSCC and the hallmark gene set were used for angiogenesis-related RiskScore model construction. The RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA), and the hallmark gene set was used to measure the angiogenesis score using the GSVA R package. Then, the optimal cutoff point for prognostic classification was calculated by the survminer package, and Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify angiogenesis gene modules . Multi/univariable and Lasso Cox analyses were performed to develop the RiskScore model, and the classifier efficiency was evaluated by the Receiver Operating Characteristic curve (ROC). Furthermore, a nomogram was designed for survival probability prediction, and the immune infiltration and immunotherapy differences among different risk patients were assessed. After calculating the angiogenesis score, we found that this indicator and patients' prognosis were closely correlated, especially when patients with a high angiogenesis score had a poor prognosis. Then, WGCNA identified a blue gene module positively correlated with angiogenesis. Multivariate and Lasso Cox analysis further identified 9 risk model genes for developing a RiskScore, which was used to divide low- and high- -risk groups of patients. Those with a high risk tended to show poor prognosis, immune infiltration, and higher immune escape. Finally, a nomogram was developed to optimize the risk model, and it exhibited excellent short- and long-term survival prediction performance. We constructed a reliable RiskScore model for the prognostic prediction of HNSCC patients, contributing to precise therapeutic intervention of the cancer.

WHO BREF Quality of Life Score as a Prognostic Indicator of Survival in Patients recovered from COVID-19 Associated Rhino-Orbito-Cerebral Mucormycosis.

Coronavirus disease 2019 (COVID-19)-associated mucormycosis (CAM) has emerged as a formidable infection in patients with COVID-19, this study was designed to assess the QOL in patients with and its predictability for survival in CAM victims. This long term prospective observational study of 290 patients with CAM was conducted over 2years using a standard questionnaire (the abbreviated World Health Organization Quality of Life questionnaire [WHO-BREF]), Karnofsky performance scale (KPS), palliative performance scale (PPS) and patient rated improvement (PRI) ranging from 0 to 9. Cut-off values of ≤ median score was considered to indicate poor QOL or poor improvement. The overall 2year survival rate was 78.27% with mean survival time of 763.2 ± 1.2days (Mean ± S.E) (95% CI: 760.76-765.6). The disease specific mortality was 22.1%. The overall mean QOL was 53.5(10.2) with 51% of population exhibiting poor QOL. Spearman rho correlation showed strong positive correlation between the three QOL scales and PRI (ρ-0.72, p < 0.001). On Cox regression analysis the stage, all four domains of WHO BREF, KPS, and PPS were independent predictors of long term survival in CAM patients. Approximately half of the patients with CAM had poor QOL and poor improvement. All 4 domains of WHO BREF score can be used as a predictor of long term survival in CAM patients. Early recognition is the key to optimal treatment, improved outcomes, and improved QOL in patients with CAM.

Analysis and prediction of long-term survival using a clinically applicable risk score based on the Electronic Health Record

BackgroundThe long-term survival of a population assigned to a hospital can be essential to anticipate, manage, and provide appropriate hospital healthcare resources or lead preventive actions for high-risk mortality individuals. In this study, we discriminate which electronic health record variables are most relevant to predict the long-term survival of a population, and apply the results to identify high-risk mortality groups. Materials and MethodsA prospective cohort study was conducted on a population of 113,403 individuals alive on July 1st, 2018 from the General Hospital of Castellón (Spain). Considering electronic health record patients’ variables and survival days from the start date of the study, a Kaplan-Meier analysis and a multivariate Cox regression model were performed, and a risk score based on Cox coefficients was applied to predict survival over 3 years. ResultsAll significant covariates from the Cox model (91.5% c-index) were associated with increased mortality risk. Using the proposed risk score, Kaplan-Meier curves show that survival probability in the 3rd year is 99.23% (95% confidence interval (CI) 99.18–99.29) for the low-risk, 91.21% (95% CI 90.67–91.76) for medium-risk, 76.52% (95% CI 75.59–77.46) for the high-risk, and 48.61 % (95% CI 46.85–50.36) for the very high-risk groups. DiscussionThe Cox model obtained is highly predictive, and it has been found that some electronic health record variables little studied to date, such as Clinical Risk Groups, have a strong impact on survival. Regarding clinical application, the proposed risk score is particularly useful for identifying high-risk subpopulations within a large population.