PIVKA-II combined with tumor burden score to predict long-term outcomes of AFP-negative hepatocellular carcinoma patients after liver resection.

BACKGROUND: This study aimed to establish a simple prognostic scoring model based on tumor burden score (TBS) and PIVKA-II to predict long-term outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients. METHODS: 511 patients were divided into the training cohort (n = 305) and the validation cohort (n = 206) at a ratio of 6:4. Receiver operating characteristic curves (ROC) were established to identify cutoff values of TBS and PIVKA-II. Kaplan-Meier curves were used to analyze survival outcomes. The multivariable Cox regression was used to identify variables independently associated with survival outcomes. The predictive performance of the TBS-PIVKA II score (TPS) model was compared with Barcelona clinic liver cancer (BCLC) stage and American Joint Committee on Cancer (AJCC TNM) stage. RESULTS: The present study established the TPS model using a simple scoring system (0, 1 for low/high TBS [cutoff value: 4.1]; 0, 1 for low/high PIVKA-II [cutoff value: 239 mAU/mL]). The TPS scoring model was divided into three levels according to the summation of TBS score and PIVKA-II score: TPS 0, TPS 1, and TPS 2. The TPS scoring model was able to stratify OS (training: p < 0.001, validation: p < 0.001) and early recurrence (training: p < 0.001; validation: p = 0.001) in the training cohort and the validation cohort. The TPS score was independently associated with OS (TPS 1 vs. 0, HR: 2.28, 95% CI: 1.01-5.17; TPS 2 vs. 0, HR: 4.21, 95% CI: 2.01-8.84) and early recurrence (TPS 1 vs. 0, HR: 3.50, 95% CI: 1.71-7.16; TPS 2 vs. 0, HR: 3.79, 95% CI: 1.86-7.75) in the training cohort. The TPS scoring model outperformed BCLC stage and AJCC TNM stage in predicting OS and early recurrence in the training cohort and the validation cohort. But the TPS scoring model was unable to stratify the late recurrence in the training cohort (p = 0.872) and the validation cohort (p = 0.458). CONCLUSIONS: The TPS model outperformed the BCLC stage and AJCC TNM stage in predicting OS and early recurrence of AFP-negative HCC patients after liver resection, which might better assist surgeons in screening AFP-negative HCC patients who may benefit from liver resection.

A new dyslipidemia-based scoring model to predict transplant-free survival in patients with hepatitis E-triggered acute-on-chronic liver failure.

BACKGROUND/AIMS: Hepatitis E virus (HEV)-triggered acute-on-chronic liver failure (ACLF) has unacceptably high short-term mortality. However, it is unclear whether the existing predictive scoring models are applicable to evaluate the prognosis of HEV-triggered ACLF. METHODS: We screened datasets of patients with HEV-triggered ACLF from a regional tertiary hospital for infectious diseases in Shanghai, China, between January 2011 and January 2021. Clinical and laboratory parameters were recorded and compared to determine a variety of short-term mortality risk factors, which were used to develop and validate a new prognostic scoring model. RESULTS: Out of 4952 HEV-infected patients, 817 patients with underlying chronic liver disease were enrolled in this study. Among these, 371 patients with HEV-triggered ACLF were identified and allocated to the training set (n = 254) and test set (n = 117). The analysis revealed that hepatic encephalopathy (HE), ascites, triacylglycerol and apolipoprotein A (apoA) were associated with 90-day mortality (P < 0.05). Based on these significant indicators, we designed and calculated a new prognostic score = 0.632 × (ascites: no, 1 point; mild to moderate, 2 points; severe, 3 points) + 0.865 × (HE: no, 1 point; grade 1-2, 2 points; grade 3-4, 3 points) - 0.413 × triacylglycerol (mmol/L) - 2.171 × apoA (g/L). Compared to four well-known prognostic models (MELD score, CTP score, CLIF-C OFs and CLIF-C ACLFs), the new scoring model is more accurate, with the highest auROCs of 0.878 and 0.896, respectively, to predict 28- and 90-day transplantation-free survival from HEV-triggered ACLF. When our model was compared to COSSH ACLF IIs, there was no significant difference. The test data also demonstrated good concordance. CONCLUSIONS: This study is one of the first to address the correlation between hepatitis E and serum lipids and provides a new simple and efficient prognostic scoring model for HEV-triggered ACLF.

A Novel Prognostic Scoring Model for Myelodysplastic Syndrome Patients With SF3B1 Mutation.

The outcomes of myelodysplastic syndrome (MDS) patients with SF3B1 mutation, despite identified as a favorable prognostic biomarker, are variable. To comprehend the heterogeneity in clinical characteristics and outcomes, we reviewed 140 MDS patients with SF3B1 mutation in Zhejiang province of China. Seventy-three (52.1%) patients diagnosed as MDS with ring sideroblasts (MDS-RS) following the 2016 World Health Organization (WHO) classification and 118 (84.3%) patients belonged to lower risk following the revised International Prognostic Scoring System (IPSS-R). Although clonal hematopoiesis-associated mutations containing TET2, ASXL1 and DNMT3A were the most frequent co-mutant genes in these patients, RUNX1, EZH2, NF1 and KRAS/NRAS mutations had significant effects on overall survival (OS). Based on that we developed a risk scoring model as IPSS-R×0.4+RUNX1×1.1+EZH2×0.6+RAS×0.9+NF1×1.6. Patients were categorized into two subgroups: low-risk (L-R, score <= 1.4) group and high risk (H-R, score > 1.4) group. The 3-year OS for the L-R and H-R groups was 91.88% (95% CI, 83.27%-100%) and 38.14% (95% CI, 24.08%-60.40%), respectively (P<0.001). This proposed model distinctly outperformed the widely used IPSS-R. In summary, we constructed and validated a personalized prediction model of MDS patients with SF3B1 mutation that can better predict the survival of these patients.

A new model based on gamma-glutamyl transpeptidase to platelet ratio (GPR) predicts prognostic outcome after curative resection of solitary hepatocellular carcinoma.

BACKGROUND: This study intends to explore the potential clinical value of gamma-glutamyl transpeptidase to platelet ratio (GPR) and the new multi-factor scoring model for recurrence and prognosis prediction in solitary HCC patients who received radical resection. METHODS: This study retrospectively analyzed 295 HCC patients after curative resection. According to the Receiver Operating Characteristic (ROC) curve, the optimal cut-off value of GPR for predicting prognosis of HCC after resection was determined. The Kaplan Meier method and Cox regression analysis were performed to assess the important potential factors in the prognosis of HCC and determine the independent risk factors. Assign a value to each independent risk factor and establish a new scoring model. Then, using GPR and the new scoring model to evaluate overall survival (OS) and postoperative recurrence probability. RESULTS: When GPR's cut-off value was selected as 0.30, its predictive efficiency for postoperative prognosis was more favorable than those of other cut-off values (0.76, 0.84 and 0.94). GPR, tumor size, microvascular invasion and neutrophil to lymphocyte ratio (NLR) were identified as independent prognostic predictors. Using these variables, a novel prognostic scoring model was devised and established to identify different levels of risk: high, intermediate and low risk groups. We found that patients with high GPR level and of high risk group would have a poorer OS and a higher recurrence rate after radical resection. CONCLUSIONS: GPR may serve as a promising predictor for postoperative prognosis and recurrence probability of HCC, and the new prognostic scoring model may be available for postoperative management among HCC patients.

Prognostic scoring models in parotid gland carcinoma.

BACKGROUND: The aim was to identify prognostic factors and test three prognostic scoring models that predicted the risk of recurrence in patients with parotid gland carcinoma. METHODS: All Danish patients with parotid gland carcinoma, treated with curative intent, from 1990 to 2015 (n = 726) were included. Potential prognostic factors were evaluated using Cox regression and competing risk analyses. The concordance of each prognostic model was estimated using Harrel's C index. RESULTS: The study population consisted of 344 men and 382 women, with a median age of 63 years. Age above 60 years, high grade histology, T3/T4 tumor, regional lymph node metastases, and involved surgical margins were all associated with a significant reduction in recurrence-free survival. The prognostic model that agreed best with actual outcomes had a C-index of 0.76. CONCLUSION: Prognostic scoring models may improve individualized follow-up strategies after curatively intended treatment for patients with parotid gland carcinoma.

Establishment of a prognostic scoring model for the breast cancer patients with spinal metastasis / 上海交通大学学报（医学版）

Objective: To explore the prognostic factors for the breast cancer patients with spinal metastasis, and establish a prognostic scoring model. Methods: A total of 160 breast cancer patients with spinal metastasis in Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from January 2008 to January 2016 were retrospectively identified. The clinical characteristics and prognosis were analyzed by univariate and multivariate survival analysis to explore the prognostic factors. And then a prognostic scoring model was developed according to the regression coefficient for each independent prognostic factor. Results: The 160 breast cancer patients with spinal metastasis whose average age was 56.8 years (range 22-82 years) were identified, and the median follow-up was 40 (24, 55) months. The multivariate Cox analysis showed that the patients' general condition, hormone receptor expression, visceral metastasis, and serum carbohydrate antigen 125 (CA125) level significantly influenced survival (P<0.05). According to the regression coefficients, a survival prediction scoring model comprising these factors was established, which ranged from 0 to 6 points. Three risk groups with different prognoses were identified : low risk group (0-1 point), intermediate risk group (2-4 points), and high risk group (5-6 points). Conclusion: The general condition, hormone receptor expression, visceral metastasis, and serum CA125 level were independent prognostic factors for the breast cancer patients with spinal metastasis. And the prognostic scoring model comprising these four clinical factors can effectively predict the patients' prognoses.

Survival of patients with metastatic leiomyosarcoma: the MD Anderson Clinical Center for targeted therapy experience.

Advanced stage leiomyosarcoma (LMS) is incurable with current systemic antitumor therapies. Therefore, there is clinical interest in exploring novel therapeutic regimens to treat LMS. We reviewed the medical records of 75 consecutive patients with histologically confirmed metastatic LMS, who had been referred to the Clinical Center for Targeted Therapy at MD Anderson Cancer Center. To lay the foundation for potential phase I trials for the treatment of advanced LMS, we analyzed tumor response and survival outcome data. The frequent hotspot gene aberrations that we observed were the TP53 mutation (65%) and RB1 loss/mutation (45%) detected by Sequenom or next-generation sequencing. Among patients treated with gene aberration-related phase I trial therapy, the median progression-free survival was 5.8 months and the median overall survival was 15.9 months, significantly better than in patients without therapy (1.9 months, P = 0.001; and 8.7 months, P = 0.013, respectively). Independent risk factors that predicted shorter overall survival included hemoglobin <10 g/dL, body mass index <30 kg/m2 , serum albumin <3.5 g/dL, and neutrophil above upper limit of normal. The median survivals were 19.9, 7.6, and 0.9 months for patients with 0, 1 or 2, and ≥3 of the above risk factors, respectively (P < 0.001). A prognostic scoring system that included four independent risk factors might predict survival in patients with metastatic LMS who were treated in a phase I trial. Gene aberration-related therapies led to significantly better clinical benefits, supporting that further exploration with novel mechanism-driven therapeutic regimens is warranted.

A distribution weighted prognostic scoring model for node status in advanced rectal cancer.

PURPOSE: There are various lymph node-based staging systems. Nevertheless, there is debate over the use of parameters such as the number of involved lymph nodes and the lymph node ratio. As a possible option, the distribution of metastatic lymph nodes may have a prognostic significance in rectal cancer. This study is designed to evaluate the impact of distribution-weighted nodal staging on oncologic outcome in rectal cancer. MATERIALS AND METHODS: From a prospectively maintained colorectal cancer database of our institution, a total of 435 patients who underwent a curative low anterior resection for mid and upper rectal cancer between 1995 and 2004 were enrolled. Patients were divided into 3 groups according to the location of apical metastatic nodes. A location-weighted prognostic score was calculated by a scoring model using a logistic regression test for location based-statistical weight to number of lymph nodes. All cases were categorized in quartiles from lymph node I to lymph node IV using this protocol. RESULTS: The location of lymph node metastasis was an independent factor that was associated with a poor prognostic outcome (p<0.001). Based on this result, the location-weighted-nodal prognostic scoring model did not show lesser significant results (p<0.0001) in both overall survival and cancer-free survival analyses. CONCLUSION: The location of apical nodes among the metastatic nodes does not have a lesser significant impact on oncologic result in patients with advanced rectal cancer. A location-weighted prognostic scoring model, which considered the numbers of involved lymph nodes as the rate of significance according to the location, may more precisely predict the survival outcome in patients with lymph node metastasis.

A Distribution Weighted Prognostic Scoring Model for Node Status in Advanced Rectal Cancer / Journal of the Korean Cancer Association, 대한암학회지

PURPOSE: There are various lymph node-based staging systems. Nevertheless, there is debate over the use of parameters such as the number of involved lymph nodes and the lymph node ratio. As a possible option, the distribution of metastatic lymph nodes may have a prognostic significance in rectal cancer. This study is designed to evaluate the impact of distribution-weighted nodal staging on oncologic outcome in rectal cancer. MATERIALS AND METHODS: From a prospectively maintained colorectal cancer database of our institution, a total of 435 patients who underwent a curative low anterior resection for mid and upper rectal cancer between 1995 and 2004 were enrolled. Patients were divided into 3 groups according to the location of apical metastatic nodes. A location-weighted prognostic score was calculated by a scoring model using a logistic regression test for location based-statistical weight to number of lymph nodes. All cases were categorized in quartiles from lymph node I to lymph node IV using this protocol. RESULTS: The location of lymph node metastasis was an independent factor that was associated with a poor prognostic outcome (p<0.001). Based on this result, the location-weighted-nodal prognostic scoring model did not show lesser significant results (p<0.0001) in both overall survival and cancer-free survival analyses. CONCLUSION: The location of apical nodes among the metastatic nodes does not have a lesser significant impact on oncologic result in patients with advanced rectal cancer. A location-weighted prognostic scoring model, which considered the numbers of involved lymph nodes as the rate of significance according to the location, may more precisely predict the survival outcome in patients with lymph node metastasis.