MELD 3.0 in Advanced Chronic Liver Disease.

The MELD (model for end-stage liver disease) 3.0 score was developed to replace the MELD-Na score that is currently used to prioritize liver allocation for cirrhotic patients awaiting liver transplantation in the United States. The MELD 3.0 calculator includes new inputs from patient sex and serum albumin levels and has new weights for serum sodium, bilirubin, international normalized ratio, and creatinine levels. It is expected that use of MELD 3.0 scores will reduce overall waitlist mortality modestly and improve access for female liver transplant candidates. The utility of MELD 3.0 and PELDcre (pediatric end-stage liver disease, creatinine) scores for risk stratification in cirrhotic patients undergoing major abdominal surgery, placement of a transjugular intrahepatic portosystemic shunt, and other interventions requires further study. This article reviews the background of the MELD score and the rationale to create MELD 3.0 as well as potential implications of using this newer risk stratification tool in clinical practice.

Immune prognostic score predicts the risk of infection and survival outcomes in patients with relapsed multiple myeloma treated with bispecific antibodies.

The Glasgow prognostic score (GPS) and CAR-HEMATOTOX (CAR-HT) score identify multiple myeloma (MM) patients at high risk for immune-mediated toxicity and early mortality with cellular immunotherapy. However, their association with outcomes in patients receiving T-cell redirecting bispecific antibodies (bsAb) is unclear. This multi-centre retrospective study examines the association of baseline GPS and CAR-HT scores with outcomes in 126 MM patients treated with bsAb. Overall, 19% were identified as GPS high risk but did not experience increased toxicity or mortality. Conversely, high-risk CAR-HT patients had a higher incidence of infections and inferior survival, suggesting a need for aggressive infection mitigation strategies.

ctDNA quantification improves estimation of outcomes in patients with high-grade osteosarcoma: a translational study from the OS2006 trial.

BACKGROUND: Osteosarcoma stratification relies on clinical parameters and histological response. We developed a new personalized stratification using less invasive circulating tumor DNA (ctDNA) quantification. PATIENTS AND METHODS: Plasma from patients homogeneously treated in the prospective protocol OS2006, at diagnosis, before surgery and end of treatment, were sequenced using low-passage whole-genome sequencing (lpWGS) for copy number alteration detection. We developed a prediction tool including ctDNA quantification and known clinical parameters to estimate patients' individual risk of event. RESULTS: ctDNA quantification at diagnosis (diagCPA) was evaluated for 183 patients of the protocol OS2006. diagCPA as a continuous variable was a major prognostic factor, independent of other clinical parameters, including metastatic status [diagCPA hazard ratio (HR) = 3.5, P = 0.002 and 3.51, P = 0.012, for progression-free survival (PFS) and overall survival (OS)]. At the time of surgery and until the end of treatment, diagCPA was also a major prognostic factor independent of histological response (diagCPA HR = 9.2, P < 0.001 and 11.6, P < 0.001, for PFS and OS). Therefore, the addition of diagCPA to metastatic status at diagnosis or poor histological response after surgery improved the prognostic stratification of patients with osteosarcoma. We developed the prediction tool PRONOS to generate individual risk estimations, showing great performance ctDNA quantification at the time of surgery and the end of treatment still required improvement to overcome the low sensitivity of lpWGS and to enable the follow-up of disease progression. CONCLUSIONS: The addition of ctDNA quantification to known risk factors improves the estimation of prognosis calculated by our prediction tool PRONOS. To confirm its value, an external validation in the Sarcoma 13 trial is underway.

Modification, validation and comparison of Naples prognostic score to determine in-hospital mortality in ST-segment elevation myocardial infarction.

AIM: The relationship between inflammatory status and poor outcomes in acute coronary syndromes is a significant area of current research. This study investigates the association between in-hospital mortality and the modified Naples prognostic score (mNPS) as well as other inflammatory biomarkers in STEMI patients. METHODS: This single-centre, cross-sectional study included 2576 consecutive STEMI patients who underwent primary percutaneous coronary intervention between January 2022 and November 2023. Participants were randomly divided into derivation and validation cohorts in a 6:4 ratio. The following inflammatory indices were calculated: pan-immune-inflammation value (PIV), systemic immune-inflammation-index (SII), systemic inflammation-response index (SIRI) and conventional NPS. The mNPS was derived by integrating hs-CRP into the conventional NPS. The performance of these indices in determining in-hospital mortality was assessed using regression, calibration, discrimination, reclassification and decision curve analyses. RESULTS: Inflammatory biomarkers, including PIV, SII, SIRI, NPS and mNPS, were significantly higher in patients who died during in-hospital follow-up compared to those discharged alive in both the derivation and validation cohorts. Multivariable logistic regression analyses were performed separately for the derivation and validation cohorts. In the derivation cohort, mNPS was associated with in-hospital mortality (aOR = 1.490, p < .001). Similarly, in the validation cohort, mNPS was associated with in-hospital mortality (aOR = 2.023, p < .001). mNPS demonstrated better discriminative and reclassification power than other inflammatory markers (p < .05 for all). Additionally, regression models incorporating mNPS were well-calibrated and showed net clinical benefit in both cohorts. CONCLUSION: mNPS may be a stronger predictor of in-hospital mortality in STEMI patients compared to the conventional scheme and other inflammatory indices.

The Glasgow Prognostic Score as a Predictor of Survival after Chemoradiotherapy for Limited-Disease Small Cell Lung Cancer.

INTRODUCTION: Established biomarkers for predicting chemoradiotherapy efficacy for limited-disease small cell lung cancer (LD-SCLC) are lacking. The inflammation-based Glasgow Prognostic Score (GPS), comprising serum C-reactive protein (CRP) and albumin levels, can predict survival in advanced cancer. This study investigated whether metabolic and inflammatory markers, including the GPS, can predict the efficacy of chemoradiotherapy in patients with LD-SCLC. METHODS: We retrospectively analyzed 124 patients who underwent chemoradiotherapy for LD-SCLC at two institutions between April 2007 and June 2021, and assessed the prognostic significance of various metabolic and inflammatory markers. The GPS was calculated using the CRP and albumin concentrations, and categorized as follows: 0, CRP <1.0 mg/dL and albumin ≥3.5 mg/dL; 1, elevated CRP or decreased albumin; and 2, CRP ≥1.0 mg/dL and albumin<3.5 mg/dL. Differences in progression-free survival (PFS) and overall survival (OS) were examined using Kaplan-Meier curves and Cox proportional-hazard models. RESULTS: The overall response rate was 95.1% (95% confidence interval [CI]: 89.6-97.9%). The median PFS and OS from chemoradiotherapy initiation were 12.6 (95% CI: 9.9-15.4) and 29.0 (95% CI: 24.8-45.5) months, respectively. The GPS demonstrated independent predictive ability for the effectiveness of chemoradiotherapy, wherein favorable scores (GPS 0-1) were significantly correlated with superior PFS and OS compared to unfavorable scores (GPS 2: PFS: 14.8 vs. 6.7 months, p = 0.0001; OS: 35.4 vs. 11.0 months, p < 0.0001). CONCLUSION: This preliminary examination revealed that the GPS was significantly associated with PFS and OS in patients undergoing chemoradiotherapy for LD-SCLC, indicating its potential utility in assessing the therapeutic outcomes in LD-SCLC.

Prognostic value of the Naples prognostic score in patients with intrahepatic cholangiocarcinoma after hepatectomy.

BACKGROUND: The Naples Prognostic Score (NPS), integrating inflammatory and nutritional biomarkers, has been reported to be associated with the prognosis of various malignancies, but there is no report on intrahepatic cholangiocarcinoma (ICC). This study aimed to explore the prognostic value of NPS in patients with ICC. METHODS: Patients with ICC after hepatectomy were collected, and divided into three groups. The prognosis factors were determined by Cox regression analysis. Predictive efficacy was evaluated by the time-dependent receiver operating characteristic (ROC) curves. RESULTS: A total of 174 patients were included (Group 1: 33 (19.0%) patients; Group 2: 83 (47.7%) patients; and Group 3: 58 (33.3%) patients). The baseline characteristics showed the higher the NPS, the higher the proportion of patients with cirrhosis and Child-Pugh B, and more advanced tumors. The Kaplan-Meier curves reflect higher NPS were associated with poor survival. Multivariable analysis showed NPS was an independent risk factor of overall survival (NPS group 2 vs. 1: HR = 1.671, 95% CI: 1.022-3.027, p = 0.009; NPS group 3 vs. 1: HR = 2.208, 95% CI: 1.259-4.780, p = 0.007) and recurrence-free survival (NPS group 2 vs. 1: HR = 1.506, 95% CI: 1.184-3.498, p = 0.010; NPS group 3 vs. 1: HR = 2.141, 95% CI: 2.519-4.087, P = 0.001). The time ROC indicated NPS was superior to other models in predicting prognosis. CONCLUSIONS: NPS is a simple and effective tool for predicting the long-term survival of patients with ICC after hepatectomy. Patients with high NPS require close follow-up, and improving NPS may prolong the survival time.

LABS score- a prognostic tool for FOLFOX4-treated advanced hepatocellular carcinoma and real-world efficacy: a single-center retrospective study.

BACKGROUND: No widely used prognostic tool exists to demonstrate the benefit of oxaliplatin plus 5-fluorouracil/leucovorin (FOLFOX4) in patients with advanced hepatocellular carcinoma (HCC). We aimed to establish a prognostic score and demonstrate the real-world efficacy of FOLFOX4 chemotherapy in Thai patients. METHODS: Between August 2017 and December 2021, we identified 58 FOLFOX4-treated patients with HCC. Overall survival (OS), progression-free survival (PFS), and objective response rate (ORR) were assessed. The prognostic score was constructed by stepwise Cox proportional hazards regression analysis to select variables for the best model with the lowest Akaike information criterion from all potential variables. RESULTS: Forty-four patients (76%) received FOLFOX4 as first-line therapy. The ORR in the entire cohort was 8.6%, and the disease control rate was 29.3%. The PFS and OS were 3.7 and 4.8 months, respectively. Four clinically relevant variables were included in the new prognostic score to predict 6-month OS: L, the presence of lung metastasis; A, alcoholic cirrhosis; B, elevated total bilirubin level; and S, sorafenib-naïve status. Using the LABS score, patients were classified into low-, intermediate-, and high-risk groups, demonstrating OS values of 9.3, 4.2, and 2.1 months, respectively (p < 0.0001). The C-index and area under the receiver-operating characteristic curve of the score were 0.71 and 0.73, respectively. CONCLUSIONS: The proposed LABS score could discriminate patients who would derive benefit from FOLFOX4 chemotherapy. FOLFOX4 chemotherapy is an option for patients who cannot receive immunotherapy and targeted therapy, particularly those with a low-risk score. However, further validation of this model via larger cohorts is warranted.

The Naples prognostic score serves as a predictor and prognostic indicator for cancer survivors in the community.

OBJECTIVE: Inflammation, malnutrition, and cancer are intricately interconnected. Despite this, only a few studies have delved into the relationship between inflammatory malnutrition and the risk of death among cancer survivors. This study aimed to specifically investigate the association between the categorically defined Naples prognostic score (NPS) and the prognosis of cancer survivors. METHODS: Data from 42,582 participants in the National Health and Nutrition Examination Survey (NHANES, 1999-2018) were subjected to analysis. Naples prognostic scores (NPS) were computed based on serum albumin (ALB), total cholesterol (TC), neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR), and participants were stratified into three groups accordingly. Cancer status was ascertained through a self-administered questionnaire, while mortality data were sourced from the National Death Index up to December 31, 2019. Multiple logistic regression was employed to estimate the odds ratio (OR) with a 95% confidence interval (CI) between NPS and cancer prevalence within the U.S. community population. Kaplan-Meier survival analysis and the Log-rank test were utilized to compare survival disparities among the three groups. Additionally, Cox proportional regression was utilized to estimate the hazard ratio (HR) with a 95% CI. RESULTS: The incidence of cancers was 9.86%. Among the participants, 8140 individuals (19.1%) were classified into Group 0 (NPS 0), 29,433 participants (69.1%) into Group 1 (NPS 1 or 2), and 5009 participants (11.8%) into Group 2 (NPS 3 or 4). After adjusting for confounding factors, the cancer prevalence for the highest NPS score yielded an odds ratio (OR) of 1.64 (95% CI: 1.36, 1.97) (P(for trend) < 0.05). In comparison to cancer survivors in Group 0, those with the highest NPS had adjusted hazard ratios (HRs) of 2.57 (95% CI: 1.73, 3.84) for all-cause mortality, 3.44 (95% CI: 1.64, 7.21) for cardiovascular mortality, 1.60 (95% CI: 1.01, 2.56) for cancer mortality, and 3.15 (95% CI: 1.74, 5.69) for other causes of mortality (All P(for trend) < 0.05). These associations remained consistent when stratified by age, sex, race, and body mass index. CONCLUSIONS: This study indicates that the Naples prognostic score (NPS), serving as a novel prognostic metric integrating inflammation and nutritional status, is closely linked to cancer prognosis within the general population.

Clinical implication of the Naples prognostic score on transcatheter aortic valve replacement in patients with severe aortic stenosis.

BACKGROUND: One of the hallmarks of frailty in patients with severe aortic stenosis (AS) is malnutrition, for which one of the most up-to-date scoring systems is the Naples prognostic score (NPS). This study sought to investigate the predictive role of the NPS in determining mortality in patients undergoing transcatheter aortic valve replacement (TAVR) under long-term follow-up. METHODS: A total of 430 consecutive patients with symptomatic severe AS who underwent TAVR were included retrospectively. The primary endpoint of the study was the long-term all-cause mortality. The study population was divided into two groups according to the NPS value, including Group 1 (NPS 0-2) and Group 2 (NPS 3-4). RESULTS: The all-cause mortality occurred in 250 patients (62.5%) patients during a follow-up time of 40.6 (22.0-69.4) months. During the follow-up period, all-cause mortality was higher in Group 2 compared with Group 1 (87.9% vs. 42.9%, p < 0.001). Older age (p < 0.001), chronic obstructive pulmonary disease (p = 0.015), left ventricular ejection fraction (p = 0.021), and being in Group 2 (high NPS) (hazard ratio: 7.058, 95% confidence interval: 5.174-9.629, p < 0.001) were found to be independent predictors of all-cause mortality at long-term follow-up. CONCLUSION: The NPS as a malnutrition and inflammation marker in patients with severe aortic stenosis who underwent TAVR provides valuable information for all-cause mortality under long-term follow-up.

Differential recall bias in estimating treatment effects in observational studies.

Observational studies are frequently used to estimate the effect of an exposure or treatment on an outcome. To obtain an unbiased estimate of the treatment effect, it is crucial to measure the exposure accurately. A common type of exposure misclassification is recall bias, which occurs in retrospective cohort studies when study subjects may inaccurately recall their past exposure. Particularly challenging is differential recall bias in the context of self-reported binary exposures, where the bias may be directional rather than random and its extent varies according to the outcomes experienced. This paper makes several contributions: (1) it establishes bounds for the average treatment effect even when a validation study is not available; (2) it proposes multiple estimation methods across various strategies predicated on different assumptions; and (3) it suggests a sensitivity analysis technique to assess the robustness of the causal conclusion, incorporating insights from prior research. The effectiveness of these methods is demonstrated through simulation studies that explore various model misspecification scenarios. These approaches are then applied to investigate the effect of childhood physical abuse on mental health in adulthood.

Prognostic score-based model averaging approach for propensity score estimation.

BACKGROUND: Propensity scores (PS) are typically evaluated using balance metrics that focus on covariate balance, often without considering their predictive power for the outcome. This approach may not always result in optimal bias reduction in the treatment effect estimate. To address this issue, evaluating covariate balance through prognostic scores, which account for the relationship between covariates and the outcome, has been proposed. Similarly, using a typical model averaging approach for PS estimation that minimizes prediction error for treatment status and covariate imbalance does not necessarily optimize PS-based confounding adjustment. As an alternative approach, using the averaged PS model that minimizes inter-group differences in the prognostic score may further reduce bias in the treatment effect estimate. Moreover, since the prognostic score is also an estimated quantity, model averaging in the prognostic scores can help identify a better prognostic score model. Utilizing the model-averaged prognostic scores as the balance metric for constructing the averaged PS model can contribute to further decreasing bias in treatment effect estimates. This paper demonstrates the effectiveness of the PS model averaging approach based on prognostic score balance and proposes a method that uses the model-averaged prognostic score as a balance metric, evaluating its performance through simulations and empirical analysis. METHODS: We conduct a series of simulations alongside an analysis of empirical observational data to compare the performances of weighted treatment effect estimates using the proposed and existing approaches. In our examination, we separately provid four candidate estimates for the PS and prognostic score models using traditional regression and machine learning methods. The model averaging of PS based on these candidate estimators is performed to either maximize the prediction accuracy of the treatment or to minimize intergroup differences in covariate distributions or prognostic scores. We also utilize not only the prognostic scores from each candidate model but also an averaged score that best predicted the outcome, for the balance assessment. RESULTS: The simulation and empirical data analysis reveal that our proposed model-averaging approaches for PS estimation consistently yield lower bias and less variability in treatment effect estimates across various scenarios compared to existing methods. Specifically, using the optimally averaged prognostic scores as a balance metric significantly improves the robustness of the weighted treatment effect estimates. DISCUSSION: The prognostic score-based model averaging approach for estimating PS can outperform existing model averaging methods. In particular, the estimator using the model averaging prognostic score as a balance metric can produce more robust estimates. Since our results are obtained under relatively simple conditions, applying them to real data analysis requires adjustments to obtain accurate estimates according to the complexity and dimensionality of the data. CONCLUSIONS: Using the prognostic score as the balance metric for the PS model averaging enhances the performance of the treatment effect estimator, which can be recommended for a wide variety of situations. When applying the proposed method to real-world data, it is important to use it in conjunction with techniques that mitigate issues arising from the complexity and high dimensionality of the data.

Alpha-fetoprotein and APRI as predictive markers for patients with Type C hepatitis B-related acute-on-chronic liver failure: a retrospective study.

BACKGROUND: Type C hepatitis B-related acute-on-chronic liver failure (HBV-ACLF), which is based on decompensated cirrhosis, has different laboratory tests, precipitating events, organ failure and clinical outcomes. The predictors of prognosis for type C HBV-ACLF patients are different from those for other subgroups. This study aimed to construct a novel, short-term prognostic score that applied serological indicators of hepatic regeneration and noninvasive assessment of liver fibrosis to predict outcomes in patients with type C HBV-ACLF. METHOD: Patients with type C HBV-ACLF were observed for 90 days. Demographic information, clinical examination, and laboratory test results of the enrolled patients were collected. Univariate and multivariate logistic regression were performed to identify independent prognostic factors and develop a novel prognostic scoring system. A receiver operating characteristic (ROC) curve was used to analyse the performance of the model. RESULTS: A total of 224 patients with type C HBV-ACLF were finally included. The overall survival rate within 90 days was 47.77%. Age, total bilirubin (TBil), international normalized ratio (INR), alpha-fetoprotein (AFP), white blood cell (WBC), serum sodium (Na), and aspartate aminotransferase/platelet ratio index (APRI) were found to be independent prognostic factors. According to the results of the logistic regression analysis, a new prognostic model (named the A3Twin score) was established. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was 0.851 [95% CI (0.801-0.901)], the sensitivity was 78.8%, and the specificity was 71.8%, which were significantly higher than those of the MELD, IMELD, MELD-Na, TACIA and COSSH-ACLF II scores (all P < 0.001). Patients with lower A3Twin scores (<-9.07) survived longer. CONCLUSIONS: A new prognostic scoring system for patients with type C HBV-ACLF based on seven routine indices was established in our study and can accurately predict short-term mortality and might be used to guide clinical management.

Association of the modified Glasgow prognostic score and prognostic nutritional index with duration of oral anamorelin administration in patients with cancer cachexia: a retrospective cohort study.

BACKGROUND: The modified Glasgow Prognostic Score (mGPS) and Prognostic Nutritional Index (PNI) are indicators of nutritional status in cancer patients; however, the effects of baseline mGPS and PNI on the duration of administration of the ghrelin receptor agonist anamorelin, which is used to treat cachexia in patients with cancer, are unclear. This study aimed to clarify the association of mGPS and PNI with the duration of oral anamorelin administration for patients who did not have beneficial effects from anamorelin. METHODS: The attending physician determined the duration of oral anamorelin administration based on discontinuation due to cancer progression, poor efficacy, adverse events, or death. RESULTS: The 12-week continuation rate of oral anamorelin was 30.4%. Univariate analysis revealed that an Eastern Cooperative Oncology Group performance status (ECOG-PS) of ≥2 (P < .001), concurrent chemotherapy (P = .002), albumin level (P = .005), C-reactive protein level (P = .013), and a mGPS of 2 (P = .014) were statistically significant predictors of the 12-week continuation rate of oral anamorelin. In the multivariate analysis, a mGPS of 2 remained a significant risk factor, and the ECOG-PS and concurrent chemotherapy had no effect on the association between the mGPS and 12-week continuation rate of oral anamorelin. CONCLUSION: Patients with a mGPS of 2, compared with mGPS of 0 or 1, are less likely to maintain oral anamorelin therapy, regardless of the ECOG-PS or concurrent chemotherapy. Therefore, it is necessary to consider initiating anamorelin administration at mGPS 0 or 1.

AFP-DIAM Score to Predict Survival in Patients with Hepatocellular Carcinoma Before TACE: A French Multicenter Study.

BACKGROUND: Transarterial chemoembolization (TACE) is recommended as a palliative treatment for patients of the B stage of the Barcelona Clinic Liver Cancer (BCLC) classification. AIMS: To identify clinical, biological, and radiological predictors of survival in patients undergoing TACE and develop a pre-therapeutic prognostic score. METHODS: 191 adult cirrhotic patients treated for HCC with TACE at the University Hospital (UH) of Clermont-Ferrand (France) from 2007-2017 were retrospectively included. We investigated the impact of baseline liver function, patient characteristics, and tumor burden on overall survival and developed a prognostic score. RESULTS: Patients had a median age of 66 years and 126 patients were Child A. The AFP-DIAM score distinguishes two groups with a significant difference in survival time (median OS 28.3 months in patients with a score = 0 versus 17.7 months in patients with a score > 0). AFP-DIAM was validated on an external cohort, is well calibrated, and has the best discrimination capacity (C-index) as compared to NIACE, HAP, STATE, and SIX TO TWELVE. AFP-DIAM and SIX TO TWELVE are the more easy-to-use scores. When AFP-DIAM and the SIX TO TWELVE scores were tested in the same statistical model, results confirmed a better AFP-DIAM performance. CONCLUSIONS: The AFP-DIAM is an easy-to-use score which allows to distinguish two groups with different prognosis before the first TACE session. Its use could provide further support to BCLC system to guide the therapeutic strategy of patients with HCC.

Rachel score: a nomogram model for predicting the prognosis of lung neuroendocrine tumors.

BACKGROUND: Lung NET, classified in typical carcinoids (TC) and atypical carcinoids (AC), are highly heterogeneous in their biology and prognosis. The histological subtype and TNM stage are well-established prognostic factors for lung NET. In a previous work by our group, we demonstrated a significant impact of laterality on lung NET survival outcomes. MATERIALS AND METHODS: We developed a nomogram that integrates relevant prognostic factors to predict lung NET outcomes. By adding the scores for each of the variables included in the model, it was possible to obtain a prognostic score (Rachel score). Wilcoxon non-parametric statistical test was applied among parameters and Harrell's concordance index was used to measure the models' predictive power. To test the discriminatory power and the predictive accuracy of the model, we calculated Gonen and Heller concordance index. Time-dependent ROC curves and their area under the curve (AUC) were used to evaluate the models' predictive performance. RESULTS: By applying Rachel score, we were able to identify three prognostic groups (specifically, high, medium and low risk). These three groups were associate to well-defined ranges of points according to the obtained nomogram (I: 0-90, II: 91-130; III: > 130 points), providing a useful tool for prognostic stratification. The overall survival (OS) and progression free survival (PFS) Kaplan-Meier curves confirmed significant differences (p < 0.0001) among the three groups identified by Rachel score. CONCLUSIONS: A prognostic nomogram was developed, incorporating variables with significant impact on lung NET survival. The nomogram showed a satisfactory and stable ability to predict OS and PFS in this population, confirming the heterogeneity beyond the histopathological diagnosis of TC vs AC.

The Hammersmith Score Optimises Patient Selection and Predicts for Overall Survival in Early-Phase Cancer Trial Participants Independent of Tumour Burden.

INTRODUCTION: As tumour response rates are increasingly demonstrated in early-phase cancer trials (EPCT), optimal patient selection and accurate prognostication are paramount. Hammersmith Score (HS), a simple prognostic index derived on routine biochemical measures (albumin <35 g/L, lactate dehydrogenase >450 IU/L, sodium <135 mmol/L), is a validated predictor of response and survival in EPCT participants. HS has not been validated in the cancer immunotherapy era. METHODS: We retrospectively analysed characteristics and outcomes of unselected referrals to our early-phase unit (12/2019-12/2022). Independent predictors for overall survival (OS) were identified from univariable and multivariable models. HS was calculated for 66 eligible trial participants and compared with the Royal Marsden Score (RMS) to predict OS. Multivariable logistic regression and C-index was used to compare predictive ability of prognostic models. RESULTS: Of 212 referrals, 147 patients were screened and 82 patients treated in EPCT. Prognostic stratification by HS identifies significant difference in median OS, and HS was confirmed as a multivariable predictor for OS (HR: HS 1 vs. 0 2.51, 95% CI: 1.01-6.24, p = 0.049; HS 2/3 vs. 0: 10.32, 95% CI: 2.15-49.62, p = 0.004; C-index 0.771) with superior multivariable predictive ability than RMS (HR: RMS 2 vs. 0/1 5.46, 95% CI: 1.12-26.57, p = 0.036; RMS 3 vs. 0/1 6.83, 95% CI: 1.15-40.53, p < 0.001; C-index 0.743). CONCLUSIONS: HS is a validated prognostic index for patients with advanced cancer treated in the context of modern EPCTs, independent of tumour burden. HS is a simple, inexpensive prognostic tool to optimise referral for EPCT.

Prognostic impact of the high-sensitivity modified glasgow prognostic score on patients undergoing radical surgery for hepatocellular carcinoma : Authorship.

OBJECTIVE: Our study aimed to assess the ability of high-sensitivity modified Glasgow prognostic Score (HS-mGPS) predicting survival in patients undergoing radical surgery for hepatocellular carcinoma (HCC) and to compare the impact with other Inflammation-Based prognostic scoring systems including Glasgow prognostic Score (GPS) and modified GPS (mGPS). METHODS: Our study evaluated 293 patients with HCC who had undergone hepatectomy at the Third Affiliated Hospital of Soochow University between 2010 and 2018. The HS-mGPS, mGPS, and GPS were calculated based on particular cut-off values of preoperative C-reactive protein and albumin, and the correlations between HS-mGPS and clinicopathological parameters were evaluated. Univariate and multivariate survival analyses were conducted by Kaplan-Meier method and Cox proportional hazards model. To evaluate the discrimination ability of each prognostic score, the receiver operating characteristic (ROC) curve were generated and the areas under the curve (AUC) were measured and compared. RESULT: The study results indicated a correlation between elevated HS-mGPS scores and adverse clinical factors, including higher BCLC stage, C-P grade, multiple tumors, and larger tumor diameter. Kaplan-Meier and univariate survival analyses revealed that higher scores of HS-mGPS, GPS, and mGPS were all associated with significantly reduced overall survival (OS) (all p < 0.001). In multivariate survival analysis, HS-mGPS emerged as an independent risk factor for poor OS in patients undergoing hepatectomy for HCC (p = 0.010), along with factors including maximal tumor diameter (p < 0.001), microvascular invasion (MVI) (p = 0.008), and BCLC stage (p = 0.001). The analysis of ROC curves and the AUC values indicated that HS-mGPS outperforms GPS and mGPS in predicting the long-term prognosis of patients with resectable HCC. CONCLUSION: Preoperative HS-mGPS proves superior in predicting adverse long-term outcomes in HCC patients undergoing radical surgery.

Predictive value of the Naples prognostic score on postoperative delirium in the elderly with gastrointestinal tumors: a retrospective cohort study.

BACKGROUND: Postoperative delirium (POD) is a common complication among elderly patients after surgery. The Naples Prognostic Score (NPS), a novel prognostic marker based on immune-inflammatory and nutritional status, was widely used in the assessment of the prognosis of surgical patients. However, no study has evaluated the relationship between NPS and POD. The aim of this article was to investigate the association between NPS and POD and test the predictive efficacy of preoperative NPS for POD in elderly patients with gastrointestinal tumors. MATERIALS AND METHODS: In the present study, we retrospectively collected perioperative data of 176 patients (≥ 60 years) who underwent elective gastrointestinal tumor surgery from June 2022 to September 2023. POD was defined according to the chart-based method and the NPS was calculated for each patient. We compared all the demographics and laboratory data between POD and non-POD groups. Univariate and multivariate logistic regression analysis was used to explore risk factors of POD. Moreover, the accuracy of NPS in predicting POD was further assessed by utilizing receiver operating characteristic (ROC) curves. RESULTS: 20 had POD (11.4%) in a total of 176 patients, with a median age of 71 (65-76). The outcomes by univariate analysis pointed out that age, ASA status ≥ 3, creatinine, white blood cell count, fasting blood glucose (FBG), and NPS were associated with the risk of POD. Multivariate logistic regression analysis further showed that age, ASA grade ≥ 3, FBG and NPS were independent risk factors of POD. Additionally, the ROC curves revealed that NPS allowed better prognostic capacity for POD than other variables with the largest area under the curve (AUC) of 0.798, sensitivity of 0.800 and specificity of 0.667, respectively. CONCLUSION: Age, ASA grade ≥ 3, and FBG were independent risk factors for POD in the elderly underwent gastrointestinal tumor surgery. Notably, the preoperative NPS was a more effective tool in predicting the incidence of POD, but prospective trials were still needed to further validate our conclusion. TRIAL REGISTRATION: The registration information for the experiment was shown below. (date: 3rd January 2024; number: ChiCTR2400079459).

Relationship of the modified Glasgow Prognostic Score with peripheral artery disease severity and procedure success in patients who had undergone endovascular treatment.

OBJECTIVES: The modified Glasgow Prognostic Score (mGPS) is one type of inflammation-based index; it includes data on elevated C-reactive protein and reduced albumin content. The predictive value of mGPS for outcomes is investigated in various diseases such as cancer, heart failure, myocardial infarction, acute pulmonary embolism, and inflammatory bowel diseases. This study aimed to evaluate the link between mGPS and the severity and complexity of peripheral arterial disease (PAD) as determined by the Transatlantic Intercommunal Consensus Document (TASC-II) classification and the prediction value of mGPS for procedural success in patients undergoing endovascular treatment (EVT). METHODS: Our study included 203 consecutive patients receiving EVT for atherosclerotic obstruction of aortoiliac, femoro-popliteal, and below-knee arteries between January 2019 and February 2020. The lesion characteristics were determined according to categories in the TASC-II. Operational failure is the inability to position the guidewire through the occluded lesion following percutaneous intervention or achieve distal perfusion following EVT. RESULTS: In our study, we observed 136 patients (%6) with TASC A-B lesions and 67 patients (%33) with TASC C-D lesions. EVT was performed on the femoro-popliteal artery in 59.4% of the patients, on the aortoiliac artery in 30.7%, and on the below-the-knee artery in 9.9%. mGPS was an independent predictor of severe PAD (OR: 17.943, 95% CI: 5.120-62.882; p < .001) and procedural success (odds ratio: 0.004; 95% CI: 0.001-0.099; p < .001). Additionally, we identified age and the presence of a TASC D lesion as independent predictors of interventional success (OR: 0.938, 95% CI: 0.819-0.979; p: .034; OR: 0.104, 95% CI: 0.107-0.643; p: .015, respectively). CONCLUSION: We determined that mGPS independently predicts PAD complexity and severity based on TASC-II classification; the EVT success rate is lower in patients with high mGPS.

Abdominal aortic calcification volume as a preoperative prognostic predictor for pancreatic cancer.

PURPOSE: Atherosclerosis and cancer may progress through common pathological factors. This study was performed to investigate the association between the abdominal aortic calcification (AAC) volume and outcomes following surgical treatment for pancreatic cancer. METHODS: The subjects of this retrospective study were 194 patients who underwent pancreatic cancer surgery between 2007 and 2020. The AAC volume was assessed through routine preoperative computed tomography. Univariate and multivariate analyses were performed to evaluate the impact of the AAC volume on oncological outcomes. RESULTS: A higher AAC volume (≥ 312 mm3) was identified in 66 (34%) patients, who were significantly older and had a higher prevalence of diabetes and sarcopenia. Univariate analysis revealed several risk factors for overall survival (OS), including male sex, an AAC volume ≥ 312 mm3, elevated carbohydrate antigen 19-9, prolonged operation time, increased intraoperative bleeding, lymph node metastasis, poor differentiation, and absence of adjuvant chemotherapy. Multivariate analysis identified an AAC volume ≥ 312 mm3, prolonged operation time, lymph node metastasis, poor differentiation, and absence of adjuvant chemotherapy as independent OS risk factors. The OS rate was significantly lower in the high AAC group than in the low AAC group. CONCLUSION: The AAC volume may serve as a preoperative prognostic indicator for patients with pancreatic cancer.