Prognostic Scoring System For Patients Research Articles

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

BackgroundType 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.MethodPatients 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.ResultsA 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.ConclusionsA 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.

Validation and comparison of prognostic scoring systems in patients with head and neck squamous cell carcinoma treated with nivolumab.

Several scoring systems have been developed to predict prognosis in patients with refractory cancer. We aimed to validate eight scoring systems and determine the best method for predicting the prognosis of head and neck squamous cell carcinoma treated with nivolumab. This multicentre retrospective study involved 154 patients with recurrent and/or metastatic head and neck squamous cell carcinoma treated with nivolumab between 2017 and 2020. Oncological outcomes were assessed according to the scoring systems, including MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio and Hammersmith scores. Objective response, overall survival and progression-free survival were evaluated using logistic regression and Cox proportional hazards analyses. Receiver operating curve analysis was used to calculate the area under the curve and estimate the efficacy of each score. No significant associations were found between the responses and any score. Seven of the eight scoring systems were associated with disease control (odds ratio, 0.26-0.70). Amongst the eight scoring systems, MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio showed the highest area under the curve for predicting response and disease control. Seven scoring systems were prognostic factors for progression-free survival (hazard ratio, 1.22-1.95). All eight scoring systems were prognostic factors for overall survival (hazard ratio, 1.62-3.83). According to the time-dependent receiver operating characteristics analysis for overall survival, the Hammersmith scoring system had the best predictive ability at 3months, and the MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio scoring system had the highest area under the curve between 6 and 24months. MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio and Hammersmith scoring systems were better predictors of prognosis in patients with head and neck squamous cell carcinoma treated with nivolumab.

A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Diffuse Large B Cell Lymphoma.

This study aimed to examine the predictive ability of inflammatory and nutritional markers and further establish a novel inflammatory nutritional prognostic scoring (INPS) system. We collected clinicopathological and baseline laboratory data of 352 patients with DLBCL between April 2010 and January 2023 at the First affiliated hospital of Ningbo University. Eligible patients were randomly divided into training and validation cohorts (n = 281 and 71, respectively) in an 8:2 ratio. We used the least absolute shrinkage and selection operator (LASSO) Cox regression model to determine the most important factors among the eight inflammatory-nutritional variables. The impact of INPS on OS was evaluated using the Kaplan-Meier curve and the Log rank test. A prognostic nomogram was developed based on the multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the nomogram. Seven inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), prognostic nutritional index (PNI), body mass index (BMI), monocyte-lymphocyte ratio (MLR), prealbumin, C reactive protein, and D-dimer were selected using the LASSO Cox analysis to construct INPS, In the multivariate analysis, IPI-High-intermediate group, IPI-High group, high INPS were independently associated with OS, respectively. The prognostic nomogram for overall survival consisting of the above two indicators showed excellent discrimination. The C-index for the nomogram was 0.94 and 0.95 in the training and validation cohorts. The time-dependent ROC curves showed that the predictive accuracy of the nomogram for OS was better than that of the NCCN-IPI system. The INPS based on seven inflammatory-nutritional indexes was a reliable and convenient predictor of outcomes in DLBCL patients.

Performance of the Molecular International Prognostic Scoring System (IPSS-M) in Hypomethylating Agent-Treated Patients with Myelodysplastic Syndromes

Background: Patients with myelodysplastic syndromes (MDS) undergo risk stratification with various prognostication tools, such as the International Prognostic Scoring System (IPSS) and Revised IPSS (IPSS-R). Recently, the Molecular IPSS (IPSS-M) was developed incorporating genomic data in addition to clinical and cytogenetic characteristics. Though IPSS-M has been shown to improve prognostication in all MDS patients at baseline, its utility in specifically patients undergoing hypomethylating agent (HMA) therapy remains unknown. Here, we assess the efficacy of IPSS-M in HMA-treated patients with MDS. Methods: We retrospectively evaluated all untreated patients with MDS seen at a single tertiary cancer center from July 2017 to July 2021 and identified those who later received HMA therapy. Patient characteristics and bone marrow (BM) data, including morphology, cytogenetics, and mutations, were assessed at diagnosis. Genomic DNA was extracted from whole BM aspirate samples and subject to 81-gene target PCR-based sequencing using a next-generation sequencing platform. Survival data was updated in July 2023. Results: Out of 799 untreated MDS patients, 455 patients (57%) eventually underwent treatment with HMA. At diagnosis, the median age was 69 (range: 22-90) with 289 (64%) male patients. Patients were generally high risk, with therapy-related MDS in 160 (35%), complex cytogenetics in 167 (37%), and TP53 mutations in 168 (37%). By IPSS-R, 259 patients (58%) had high- or very high-risk disease, and 340 patients (75%) had higher-risk disease (moderate high-, high-, and very high-risk) by IPSS-M. A total of 291 patients (64%) were treated with HMA monotherapy, and lower-risk MDS patients received more cycles of HMA (p &amp;lt; 0.001). By IPSS-R, the median overall survival was 60.0 months (95% CI: 46.0, not estimable (NE)) in very low-, 87.4 months (95% CI: 59.9, NE) in low-, 36.2 months (95% CI: 30.0, 58.1) in intermediate-, 23.7 months (95% CI: 19.6, 34.8), in high-, and 12.8 months (95% CI: 11.0, 16.7) in very high-risk patients (p &amp;lt; 0.0001) with a concordance index of 0.669. Figure 1 depicts the reclassification of patients between IPSS-R and IPSS-M. Risk stratification by IPSS-M (Figure 2) provided similar results: not reached (95% CI: 56.8, NE) in very low-, 60.0 months (95% CI: 49.8, NE) in low-, 40.8 months (95% CI: 22.8, NE) in moderate low-, 44.2 months (95% CI: 27.8, NE) in moderate high-, 33.4 months (95% CI: 22.8, 44.5) in high-, and 16.6 months (95% CI: 13.8, 19.4) in very high-risk patients (p &amp;lt; 0.0001). The concordance index of IPSS-M in all HMA-treated MDS patients was 0.648. When analyzing patients with MDS who were more likely to undergo HMA as per standard-of-care treatment (those with IPSS-M moderate low-, moderate high-, high-, and very high-risk disease), the IPSS-M remained statistically significant (p &amp;lt; 0.0001) though less discerning in the patients with moderate-risk MDS, as seen by the concordance index of 0.620. Conclusions: In this group of MDS patients treated with HMA, the IPSS-M did not provide additional prognostic power over the IPSS-R though median overall survival remained inversely proportional to IPSS-M risk category. Concordance indices for survival remained below 0.7, likely due to the overlapping curves in moderate-risk patients by IPSS-M. Further development and validation of prognostic scoring systems in patients treated with HMA are warranted.

Utility of Established Prognostic Scoring Systems for Patients with Advanced Pancreatic Adenocarcinoma Enrolled in Immunotherapy-Based Early-Phase Clinical Trials.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy for which multiagent chemotherapy is the mainstay of treatment resulting in limited survival and symptomatic benefit. Treatment with immune checkpoint inhibitors (ICI) has proven effective in a growing number of solid tumors but has yet to show clinical benefit in patients with PDAC. Given the growing number of ICI-based clinical trials in development for patients with PDAC and lack of clinical benefit thus far with ICI-based therapies in these patients, we sought to (1) determine the outcomes of patients with PDAC treated with ICI-based therapies as part of an early phase clinical trial, (2) validate the utility of established prognostic scoring systems, and (3) identify novel prognostic factors in an attempt to better identify patients that would benefit from enrollment onto an ICI-based early phase clinical trial. We conducted a single-center retrospective analysis of patients with advanced PDAC who were treated with ICI-based therapy as part of an early-phase clinical trial. Patients were only able to stay on study for a limited time due to disease progression and/or a change in performance status and had a poor overall survival. Established prognostic scoring systems were not effective in predicting outcomes in this patient population, but factors such as pre-treatment albumin neutrophil to lymphocyte ratio (NLC) may be helpful in patient selection. This study underscores the need for larger studies to help identify patient and tumor intrinsic factors that predict response to ICI-based therapies in patients with PDAC.

Evaluation of prognostic scoring systems in patients hospitalized from the emergency department in a low-income region: northern Syria after internal turmoil as a different universe.

In low-income or underdeveloped countries with conflict and internal unrest, healthcare facilities and staff are limited. For these reasons, it is necessary to use the most straightforward scoring systems to ensure that health facilities and staff are used effectively and to expedite processes through early and effective interventions for patients. In this study, we evaluate and compare the scoring systems used to predict patient prognosis for Emergency Department (ED) patients in northern Syria, which is an area marred by conflict and internal unrest. In this study, patients hospitalized in the Afrin, Azez Vatan, Jarablus, Tel Abyad, Rasulayn, El Bab, and Çobanbey hospitals in northern Syria were investigated. Only patients that were hospitalized in the emergency departments of these hospitals, including wards and intensive care units, were included in the study. Patients that were hospitalized from 03/01/2021 to 08/31/2021, the study period, were prospectively analyzed. Vital signs, medical histories and demographic data of the patients were recorded by calculating National Early Warning Score 2 (NEWS2), Rapid Acute Physiology Score (RAPS), Rapid Emergency Medicine Score (REMS), and HOTEL Score (hypotension, oxygen saturation, low temperature, electrocardiogram, loss of independence). Acceptance parameters and scores were analyzed using statistical methods and by comparing groups. : All four scoring systems were found to be effective in predicting mortality regarding ROC curve analysis. However, the statistical significance of the RAPS was slightly stronger than that of the other scores and REMS had the highest sensitivity and specificity amongst the four systems, at 86.2% and 84.1%, respectively. Regarding the risk of hospitalization in the ICU (p < 0.05), the sensitivity values of the cut-off values offered by the scoring systems remained below 0.70 regarding ROC curve analysis. RAPS had the highest sensitivity (65.2%) of the four systems with a cut-off value of 1.5. This study in northern Syria has shown that although RAPS had stronger statistical power, REMS had better sensitivity and specificity for the prediction of mortality. Additionally, RAPS had better sensitivity for ICU risk. This study will contribute to the evaluation of healthcare in similar regions and to cost-effective healthcare delivery by using scoring systems for ED patients' admission.

Predictive value of prognostic inflammatory and tumor score in intrahepatic cholangiocarcinoma

Objective: To compare and analyze the predictive value of different inflammatory factors and tumor markers in intrahepatic cholangiocarcinoma and to develop a new and effective preoperative prognostic scoring system. Methods: 102 and 72 cases with intrahepatic cholangiocarcinoma who underwent radical surgery in Tianjin Medical University Cancer Institute and Hospital and the Affiliated Hospital of Weifang Medical University were selected as the experimental group and the validation group, respectively. Clinicopathological and follow-up data were collected. Cox proportional-hazards model was used to analyze the predictive value of different prognostic markers. The relationship between prognostic markers and clinicopathological data was analyzed by rank sum test, χ2 or Fisher's exact test. Results: Among the direct inflammatory factors, tumor markers and combined inflammatory factors, prognostic inflammatory index (PII), carbohydrate antigen (CA) 19-9 and systemic inflammation score (SIS) were the most significant predictive factors for postoperative survival outcomes in patients with intrahepatic cholangiocarcinoma. The prognostic inflammatory and tumor score (PITS) was proposed as a new prognostic scoring system for intrahepatic cholangiocarcinoma. PII and CA19-9 were included into the scoring criteria for prognostic stratification of patients. PITS was an independent predictor of tumor-free survival and overall survival in patients with intrahepatic cholangiocarcinoma. Patients with high-grade PITS had later tumor grade and higher frequency of vascular invasion. Conclusion: PITS is highly effective prognostic scoring system for patients with intrahepatic cholangiocarcinoma. In addition, PITS is recommended for preoperative prognostic stratification in patients with intrahepatic cholangiocarcinoma.

Short-Term Prognostic Efficacy of mGPS and LCS in Patients With Acute Heart Failure.

AimSystemic inflammation plays an important role in the occurrence and development of acute heart failure. The modified Glasgow Prognostic Score (mGPS) and “lymphocyte C-reactive protein score” (LCS) are used to assess the inflammation levels in cancer patients. The purpose of this study was to assess the prognostic value of these two inflammation-related scoring systems in patients with acute heart failure.MethodsTwo hundred and fifty patients with acute heart failure were enrolled in this study. The mGPS and LCS scores were recorded after admission. All patients were divided into 2 groups: the death group and the survival group according to the 3-month follow-up results. The predictive values of mGPS and LCS were assessed using receiver-operating characteristic (ROC) analyses. Univariate and multivariate logistic analyses were used to evaluate the relationships between variables and endpoint.ResultsThe levels of mGPS and LCS in the death group were significantly higher than those in the survival group (P < 0.05). The areas under the ROC curve of the mGPS and LCS for predicting death were 0.695 (95%CI: 0.567~0.823) and 0.736 (95%CI: 0.616~0.856), respectively. Multivariate analysis demonstrated that both LCS, LVEF and serum direct bilirubin were independent predictors of all-cause death, excluding mGPS.ConclusionsCompared with mGPS, LCS is independently associated with short-term outcomes in patients with acute heart failure. LCS was a clinically promising and feasible prognostic scoring system for patients with acute heart failure.

Development and validation of a prognostic scoring system for patients with colorectal cancer hepato-pulmonary metastasis: a retrospective study

BackgroundHepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM).MethodsWe retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients.ResultsA nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics.ConclusionA nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients.

A Nutritional Metabolism Related Prognostic Scoring System for Patients With Newly Diagnosed Osteosarcoma

Osteosarcoma is a primary malignant bone tumor with high metastatic potential. To date, achieving long-term survival of osteosarcoma patients remains a difficult task. Metabolic reprogramming has emerged as a new hallmark of cancer. However, studies on the prognostic value of hematological markers related to nutritional and metabolism in cancer patients are limited and contradictory. In this retrospective study, we extensively collected 16 hematological markers related to nutritional and metabolism in 223 osteosarcoma patients. A nutritional metabolism related prognostic scoring system (NMRS) in patients with osteosarcoma was constructed by least absolute contraction and selection operator (LASSO) cox regression analysis. Compared with individual hematological indicators, NMRS has stronger predictive power (training set: 0.811 vs. 0.362–2.638; validation set: 0.767 vs. 0.333–0.595). It is an independent prognostic factor for the survival of patients with osteosarcoma [HR: 1.957 (1.375–2.786) training set; HR: 3.146 (1.574–6.266) validation set]. NMRS-based nomograms have good and stable predictive power. NMRS facilitates further risk stratification of patients with the same clinical characteristics.

A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Early-Stage Breast Cancer.

PurposeWe attempted to explore the prognostic value of baseline inflammatory and nutritional biomarkers at diagnosis in patients with early-stage breast cancer and develop a novel scoring system, the inflammatory-nutritional prognostic score (INPS).Patients and MethodsWe collected clinicopathological and baseline laboratory data of 1259 patients with early-stage breast cancer between December 2010 and November 2012 from Sun Yat-sen University Cancer Center. Eligible patients were randomly divided into training and validation cohorts (n = 883 and 376, respectively) in a 7:3 ratio. We selected the most valuable biomarkers to develop INPS by the least absolute shrinkage and selection operator (LASSO) Cox regression model. A prognostic nomogram incorporating INPS and other independent clinicopathological factors was developed based on the stepwise multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the predictive nomogram.ResultsFour inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), prognostic nutritional index (PNI), and albumin-alkaline phosphatase ratio (AAPR), were selected using the LASSO Cox analysis to construct INPS, which remained an independent prognostic indicator per the multivariate Cox regression analysis. Patients were stratified into low- and high-INPS groups based on the cutoff INPS determined by the maximally selected rank statistics. The prognostic model for overall survival consisting of INPS and other independent clinicopathological indicators showed excellent discrimination with C-indexes of 0.825 (95% confidence interval [CI]: 0.786–0.864) and 0.740 (95% CI: 0.657–0.822) in the training and validation cohorts, respectively. The time-dependent ROC curves showed a higher predictive accuracy of our prognostic nomogram than that of traditional tumor-node-metastasis staging.ConclusionBaseline INPS is an independent indicator of OS in patients with early-stage breast cancer. The INPS-based prognostic nomogram could be used as a practical tool for individualized prognostic predictions.

Comparison of the Efficacy of Balthazar Score and C-Reactive Protein-Albumin Ratio for Determination of Acute Pancreatitis Severity.

Acute pancreatitis (AP) clinic has a wide spectrum ranging from asymptomatic cases to mortality. Early diagnosis and prediction are of great importance to prevent mortality in AP patients. Many prognostic scoring systems have been developed for AP to date. At the time of the initial assessment of attendance to the emergency department (ED), it is impractical to use existing prognostic scoring systems for patients with a diagnosis of AP in most patients. The prognostic performances of radiological and clinical scoring systems of 329 patients diagnosed with acute pancreatitis were compared in terms of C-reactive protein-albumin ratio (CAR) levels, mortality and severity according to Balthazar score. It was observed that the CAR value increased as the AP severity increased. For mortality estimation, the ROC curve was used for sensitivity, specificity, and cut-off values for each scoring system for CAR. When mild pancreatitis and severe pancreatitis were compared according to Balthazar score, the differences between CAR were statistically significant and positive correlations were present. The CAR value has been shown to be a useful clinical tool that can be used with its high predictive value. CAR has the advantages of being easily accessible, inexpensive, and having moderately high diagnostic power to predict AP severity.

A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma.

BackgroundGlioblastoma is the most common primary malignant brain tumor. Recent studies have shown that hematological biomarkers have become a powerful tool for predicting the prognosis of patients with cancer. However, most studies have only investigated the prognostic value of unilateral hematological markers. Therefore, we aimed to establish a comprehensive prognostic scoring system containing hematological markers to improve the prognostic prediction in patients with glioblastoma.Patients and MethodsA total of 326 patients with glioblastoma were randomly divided into a training set and external validation set to develop and validate a hematological-related prognostic scoring system (HRPSS). The least absolute shrinkage and selection operator Cox proportional hazards regression analysis was used to determine the optimal covariates that constructed the scoring system. Furthermore, a quantitative survival-predicting nomogram was constructed based on the hematological risk score (HRS) derived from the HRPSS. The results of the nomogram were validated using bootstrap resampling and the external validation set. Finally, we further explored the relationship between the HRS and clinical prognostic factors.ResultsThe optimal cutoff value for the HRS was 0.839. The patients were successfully classified into different prognostic groups based on their HRSs (P < 0.001). The areas under the curve (AUCs) of the HRS were 0.67, 0.73, and 0.78 at 0.5, 1, and 2 years, respectively. Additionally, the 0.5-, 1-y, and 2-y AUCs of the HRS were 0.51, 0.70, and 0.79, respectively, which validated the robust prognostic performance of the HRS in the external validation set. Based on both univariate and multivariate analyses, the HRS possessed a strong ability to predict overall survival in both the training set and validation set. The nomogram based on the HRS displayed good discrimination with a C-index of 0.81 and good calibration. In the validation cohort, a high C-index value of 0.82 could still be achieved. In all the data, the HRS showed specific correlations with age, first presenting symptoms, isocitrate dehydrogenase mutation status and tumor location, and successfully stratified them into different risk subgroups.ConclusionsThe HRPSS is a powerful tool for accurate prognostic prediction in patients with newly diagnosed glioblastoma.

Value of Liver Regeneration in Predicting Short-Term Prognosis for Patients with Hepatitis B-Related Acute-on-Chronic Liver Failure.

Background and Aims The value of hepatocyte regeneration in predicting the outcomes of hepatitis B-related acute-on-chronic liver failure (HBV-ACLF) is not fully assessed. The present study was aimed at establishing a novel scoring system to predict patients' outcomes within 3 months by applying serological indicators of hepatic regeneration and liver injury. Methods Patients with chronic hepatitis B who had a rapid deterioration were investigated. Patients were observed for 90 days, and the endpoint of follow-up was death or liver transplantation. Serum parameters were estimated on the diagnosis of acute-on-chronic liver failure (ACLF). Cox proportional hazard regression was used to identify independent prognostic factors and create a novel prognostic scoring system, and a receiver operating characteristic (ROC) curve was used to analyze the performance of the model. Results A total of 308 patients with HBV-ACLF were incorporated and divided into the training cohort (n = 206) and testing cohort (n = 102) randomly. Creatine (Cre), age, total bilirubin (TBil), alpha-fetoprotein (AFP), and international normalized ratio (INR) were found to be independent prognostic factors. According to the results of Cox regression analysis, a new prognostic model (we named it the TACIA score) was calculated. The areas under ROC (AUROC) for the new model were 0.861 and 0.763 in the training and testing cohorts, respectively, and patients with lower TACIA scores (<4.34) would survive longer (P < 0.001). Conclusions A pertinent prognostic scoring system for patients with HBV-ACLF was established in our study, and the novel model could predict patients' short-term survival effectively.

Application and Comparison of Different Prognostic Scoring Systems in Patients Who Underwent Cardiologist-Managed Percutaneous Cardiopulmonary Support.

Temporary mechanical support, including percutaneous cardiopulmonary support (PCPS), is crucial for reversing patients' compromised hemodynamic function. Knowledge about whether cardiologists can directly manage patients receiving PCPS and about the predictive values of different prognostic scores is insufficient. We examined the data and in-hospital mortality of 45 eligible patients receiving cardiologist-managed PCPS from July 2012 to January 2019 in our institute. We compared different prognostic scores [namely Survival After Veno-arterial ECMO (SAVE), modified SAVE, prEdictioN of Cardiogenic shock OUtcome foR acute myocardial infarction patients salvaGed by VA-ECMO (ENCOURAGE), and Sequential Organ Failure Assessment (SOFA) scores] through area under the receiver operating characteristic curve (AUC) analysis. The patients' mean age was 64.3 ± 11.3 years, and 71.1% were men. The overall in-hospital survival rate was 35.6%. Compared to survivors, nonsurvivors were more likely to have an ischemic etiology, cardiopulmonary resuscitation, and higher lactate levels. Survivors had higher SAVE (-5.9 vs. -11.4) and modified SAVE (4.2 vs. -7.1) scores than nonsurvivors (both p = 0.001), but SOFA (9.7 vs. 10.3) and ENCOURAGE (24.8 vs. 26.8) scores were similar (both p > 0.1). In multivariate models, only modified SAVE score remained statistically significant (hazard ratio: 0.96, 95% confidence interval: 0.93-1.00; p = 0.047). Modified SAVE score showed the best risk discrimination (AUC = 0.78). Establishing regular and continual training protocols can enable cardiologists to perform emergency PCPS (without on-site surgery) and daily care for patients with refractory cardiogenic shock. The modified SAVE score facilitates risk stratification and future decision-making processes.

The Functional Palliative Prognostic Index: a scoring system for functional prognostication of patients with advanced cancer.

For appropriate advance care planning, functional prognostication is necessary. However, there are no studies of functional prognostication in patients with cancer. The aim of this study was to develop a functional prognostic scoring system for patients with advanced cancer. In this multicenter prospective observational study, 1896 patients were enrolled. First, Cox regression analysis and the combination of forward and backward variable selection were used to identify the best subset of predictors. Second, the prognostic score value was defined from each regression coefficient of a significant prognostic factor. The Functional Palliative Prognostic Index (FPPI) was calculated by summing the prognostic scores. Patients were classified into three groups by the FPPI. For walking, the 14-day functional survival probability was > 72.8% for group A (score 0), 28.4-72.8% for group B (score 1), and < 28.4% for group C (score 2-3). For eating, the 14-day functional survival probability was > 71.8% for group A (score 0-3), 29.6-71.8% for group B (score 3.5-5.5), and < 29.6% for group C (score 6-9). For communicating, the 14-day functional survival probability was > 76.6% for group A (score 0-6.5), 22.6-76.6% for group B (score 7-10), and < 22.6% for group C (score 10.5-16). Regarding each item, group B functionally survived significantly longer than group C, and group A functionally survived significantly longer than either of the others. We firstly developed a functional prognostic scoring system for patients with advanced cancer. This FPPI system promises to be helpful in advance care planning.

Validation of prognostic scoring systems for patients with metastatic renal cell carcinoma enrolled in phase I clinical trials

BackgroundFor patients with metastatic renal cell carcinoma (mRCC) who progress on standard-of-care therapies, there is an unmet need for novel treatments. Phase I clinical trials are designed to test the safety, toxicity and optimal dosing of novel agents. Herein, we analysed the outcomes of patients with mRCC enrolled in phase I trials and assess the utility of prognostic scores.MethodsPatients with all histologies of mRCC were included if they received treatment on a phase I clinical trial at MD Anderson Cancer Center (MDACC). Survival outcomes were calculated using Cox proportional hazard model. Prognostic value of the International Metastatic RCC Database Consortium (IMDC), Royal Marsden Hospital (RMH) and MDACC scores was assessed using the likelihood ratio (LR) χ2 test and the c-index.ResultsAmong 82 patients with mRCC who received treatment, 21 patients participated in more than one trial, resulting in 106 trial participants (TP). Median prior therapies was two. For all TPs, median overall survival (OS) was 31.2 months, progression-free survival (PFS) was 5.9 months and objective response rate was 22%. Median OS and PFS were significantly shorter with increasing IMDC, RMH and MDACC scores. The RMH and MDACC scores outperformed the IMDC score for predicting OS (RMH LR χ2=8.64; MDACC LR χ2=7.74; IMDC LR χ2=2.36) and PFS (RMH LR χ2=17.5; MDACC LR χ2=20.3; IMDC LR χ2=4.28).ConclusionsThe RMH and MDACC prognostic scores can be used to predict OS for patients with mRCC in phase I trials and may guide patient selection. Patients with mRCC should be considered for phase I trials.

03:36 PM Abstract No. 232 Evaluation of a new prognostic scoring system for hepatocellular carcinoma patients and portal vein invasion treated with radioembolization in a 152-patient cohort

To evaluate a new prognostic scoring system to delineate survival benefit for patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombosis (PVTT) undergoing ytrrium-90 radioembolization (Y90). With IRB approval, a retrospective chart review (2004-2017) of HCC patients (Child-Pugh A-B7) with PVTT and no extra-hepatic metastases at time of Y90 was performed. We employed a recently published prognostic system (Spreafico et al., Journal of Hepatology, 2018) to stratify outcomes with 3 variables: Baseline tumor burden (visual estimation): < 50% tumor burden =0 and >50% tumor burden =3; Serum bilirubin: ≤ 1.2 mg/dl =0 and >1.2 mg/dl =2; Portal vein involvement: segmental PVTT =0, lobar PVTT =2, and main portal or superior mesenteric vein tumor thrombosis =3. Three prognostic subgroups were created from total score: favorable (0-1 points), intermediate (2-3 points), and poor (> 3 points) prognosis. The hazard ratio (HR) comparing each subgroup was calculated. Overall survival (OS) was evaluated with Kaplan-Meier analysis. 152 patients met inclusion criteria; 16% were alive at date of data extraction. Median OS of cohort was 8.7 (95% CI, 7.7-11.4). Median OS for prognostic subgroups were: favorable (n=35, 23%) 13.3 (95% CI, 8.0-15.6), intermediate (n=82, 54%) 9.1 (95% CI, 7.7-14.2), and poor (n=35, 23%) 5.3 (95% CI, 4.1-8.4) months, respectively. These numbers are lower than Spreafico et al: Median OS in 3 categories was 32.2, 14.9 and 7.8 months, respectively. The HR of the favorable subgroup was 1.1 and 1.9 compared to intermediate and poor subgroups, respectively (p<0.05). The HR of the intermediate subgroup was 0.95 and 1.8 compared to favorable and poor subgroups, respectively (p<0.05). The poor subgroup HR was 0.53 and 0.56 compared to favorable and intermediate subgroups, respectively (p<0.05). A prognostic scoring system for patients with HCC and PVTT including serum bilirubin, tumor burden, and level of PVT can delineate survival benefit from Y90. However, we are unable to replicate outcomes by the Spreafico group. Further patient stratification might be required to validate this novel system. be required to validate this novel system.

Development of a risk scoring system for patients with papillary thyroid cancer.

As the importance of personalized therapeutics in aggressive papillary thyroid cancer (PTC) increases, accurate risk stratification is required. To develop a novel prognostic scoring system for patients with PTC (n = 455), we used mRNA expression and clinical data from The Cancer Genome Atlas. We performed variable selection using Network‐Regularized high‐dimensional Cox‐regression with gene network from pathway databases. The risk score was calculated using a linear combination of regression coefficients and mRNA expressions. The risk score and clinical variables were assessed by several survival analyses. The risk score showed high discriminatory power for the prediction of event‐free survival as well as the presence of metastasis. In multivariate analysis, the risk score and presence of metastasis were significant risk factors among the clinical variables that were examined together. In the current study, we developed a risk scoring system that will help to identify suitable therapeutic options for PTC.

Prognostic scoring system for osteosarcoma using network-regularized high-dimensional Cox-regression analysis and potential therapeutic targets.

With the recent emphasis on the importance of personalized genomic medicine, studies have performed prognostic stratification using gene signatures in cancers. However, these studies have not considered gene networks with clinical data. Therefore, this study aimed to develop a novel prognostic score using grouped variable selection for patients with osteosarcoma. We assessed messenger RNA (mRNA) expression and clinical data from Gene Expression Omnibus to develop a novel prognostic scoring system for patients with osteosarcoma. Variable selection using Network-Regularized high-dimensional Cox-regression analysis with information regarding gene networks obtained from six large pathway databases was performed. We determined the risk score on the linear combination of regression coefficients and mRNA expression values. Log-rank test, UNO's c-index, and area under the curve (AUC) values were determined to evaluate the discriminatory power between the low- and high-risk groups. A recently reported next-generation Connectivity Map was used to identify future therapeutic targets for osteosarcoma. Our novel model had significantly high discriminatory power in predicting overall survival. An optimal c-index of 0.967 was obtained and time-dependent receiver operating characteristic analysis revealed an acceptable predictive value of AUC between 0.953 and 1.000. Knockdown of BACE2 or ING2 and linifanib treatment may improve the prognosis of patients with osteosarcoma. Herein, this novel prognostic scoring system would not only facilitate a more accurate prediction of patient prognosis, but also contribute to the selection of suitable therapeutic alternatives for osteosarcoma patients.