Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

Development of a novel staging classification for Siewert II adenocarcinoma of the esophagogastric junction after neoadjuvant chemotherapy

BACKGROUND

Stage classification for Siewert II adenocarcinoma of the esophagogastric junction (AEG) treated with neoadjuvant chemotherapy (NAC) has not been established.

AIM

To investigate the optimal stage classification for Siewert II AEG with NAC.

METHODS

A nomogram was established based on Cox regression model that analyzed variables associated with overall survival (OS) and disease-specific survival (DSS). The nomogram performance in terms of discrimination and calibration ability was evaluated using the likelihood-ratio test, Akaike information criterion, Harrell concordance index, time-receiver operating characteristic curve, and decision curve analysis.

RESULTS

Data from 725 patients with Siewert type II AEG who underwent neoadjuvant therapy and gastrectomy were obtained from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate analyses revealed that sex, marital status, race, ypT stage, and ypN stage were independent prognostic factors of OS, whereas sex, race, ypT stage, and ypN stage were independent prognostic factors for DSS. These factors were incorporated into the OS and DSS nomograms. Our novel nomogram model performed better in terms of OS and DSS prediction compared to the 8^th American Joint Committee of Cancer pathological staging system for esophageal and gastric cancer. Finally, a user-friendly web application was developed for clinical use.

CONCLUSION

The nomogram established specifically for patients with Siewert type II AEG receiving NAC demonstrated good prognostic performance. Validation using external data is warranted before its widespread clinical application.

Development of a novel staging classification for Siewert II adenocarcinoma of the esophagogastric junction after neoadjuvant chemotherapy

BACKGROUND

Stage classification for Siewert II adenocarcinoma of the esophagogastric junction (AEG) treated with neoadjuvant chemotherapy (NAC) has not been established.

AIM

To investigate the optimal stage classification for Siewert II AEG with NAC.

METHODS

A nomogram was established based on Cox regression model that analyzed variables associated with overall survival (OS) and disease-specific survival (DSS). The nomogram performance in terms of discrimination and calibration ability was evaluated using the likelihood-ratio test, Akaike information criterion, Harrell concordance index, time-receiver operating characteristic curve, and decision curve analysis.

RESULTS

Data from 725 patients with Siewert type II AEG who underwent neoadjuvant therapy and gastrectomy were obtained from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate analyses revealed that sex, marital status, race, ypT stage, and ypN stage were independent prognostic factors of OS, whereas sex, race, ypT stage, and ypN stage were independent prognostic factors for DSS. These factors were incorporated into the OS and DSS nomograms. Our novel nomogram model performed better in terms of OS and DSS prediction compared to the 8th American Joint Committee of Cancer pathological staging system for esophageal and gastric cancer. Finally, a user-friendly web application was developed for clinical use.

CONCLUSION

The nomogram established specifically for patients with Siewert type II AEG receiving NAC demonstrated good prognostic performance. Validation using external data is warranted before its widespread clinical application.

Identification and validation of key miRNAs and a microRNA-mRNA regulatory network associated with liver cancer

MiRNAs play crucial regulatory roles in the growth and development of tumor cells by serving as carriers of post-transcriptional regulatory information derived from genes. Investigating the potential function and clinical significance of miRNA-mediated mRNA regulatory networks in liver cancer can offer novel insights and therapeutic strategies for the treatment of this disease. We identified 300 differentially expressed miRNAs, and five miRNAs were identified to be correlated with overall survival and could be used as an independent prognostic. GO enrichment analysis mainly included carboxylic acid biosynthesis, organic acid biosynthesis, peroxisomal membrane, microsomal membrane, DNA binding, C-acyltransferase activity, etc. KEGG enrichment analysis showed that the pathways of target genes related to liver cancer were mainly focused on butyric acid metabolism and partial amino acid metabolism. Eight of the top 10 HUB genes were associated with prognosis, and the expression of four genes was positively correlated with prognosis, of which ABAT, BHMT, and SHMT1 were target genes of hsa-miR-5003-3p. MiR-5003-3p inhibits ABAT/BHMT/SHMT1 expression, thereby promoting liver cancer development. Overall, our study provides new ideas for the treatment of liver cancer, and these five miRNAs may be independent prognostic biomarkers and therapeutic targets for liver cancer patients. And miR-5003-3p may be a critical factor in the mechanism of liver cancer development.

Inference for covariate-adjusted time-dependent prognostic accuracy measures

Evaluating the prognostic performance of candidate markers for future disease onset or progression is one of the major goals in medical research. A marker's prognostic performance refers to how well it separates patients at the high or low risk of a future disease state. Often the discriminative performance of a marker is affected by the patient characteristics (covariates). Time-dependent receiver operating characteristic (ROC) curves that ignore the informativeness of the covariates will lead to biased estimates of the accuracy parameters. We propose a time-dependent ROC curve that accounts for the informativeness of the covariates in the case of censored data. We propose inverse probability weighted (IPW) estimators for estimating the proposed accuracy parameters. We investigate the performance of the IPW estimators through simulation studies and real-life data analysis.

Characterization of tumor microenvironment and tumor immunology based on the double-stranded RNA-binding protein related genes in cervical cancer

BACKGROUND

Cervical cancer is one of the most common gynecological cancers threatening women's health worldwide. Double-stranded RNA-binding proteins (dsRBPs) regulate innate immunity and are therefore believed to be involved in virus-related malignancies, however, their role in cervical cancer is not well known.

METHODS

We performed RNA-seq of tumor samples from cervical cancer patients in local cohort and also assessed the RNA-seq and clinical data derived from public datasets. By using single sample Gene Set Enrichment Analysis (ssGSEA) and univariate Cox analysis, patients were stratified into distinct dsRBP clusters. Stepwise Cox and CoxBoost were performed to construct a risk model based on optimal dsRBPs clusters-related differentially expressed genes (DEGs), and GSE44001 and CGCI-HTMCP-CC were employed as two external validation cohorts. Single cell RNA sequencing data from GSE168652 and Scissor algorithm were applied to evaluated the signature-related cell population.

RESULTS

The expression of dsRBP features was found to be associated with HPV infection and carcinogenesis in CESC. However, only Adenosine deaminases acting on RNA (ADAR) and Dicer, Drosha, and Argonautes (DDR) exhibited significant correlations with the overall survival (OS) of CESC patients. Based on these findings, CESC patients were divided into three dsRBP clusters. Cluster 3 showed superior OS but lower levels of ADAR and DDR. Additionally, Cluster 3 demonstrated enhanced innate immunity, with significantly higher activity in cancer immunity cycles, immune scores, and levels of tumor-infiltrating immune cells, particularly CD8+ T cells. Furthermore, a risk model based on nine dsRBP cluster-related DEGs was established. The accuracy of survival prediction for 1 to 5 years was consistently above 0.78, and this model's robust predictive capacity was confirmed by two external validation sets. The low-risk group exhibited significantly higher levels of immune checkpoints, such as PDCD1 and CTLA4, as well as a higher abundance of CD8+ T cells. Analysis of single-cell sequencing data revealed a significant association between the dsRBP signature and glycolysis. Importantly, low-risk patients showed improved OS and a higher response rate to immunotherapy, along with enduring clinical benefits from concurrent chemoradiotherapy.

CONCLUSIONS

dsRBP played a crucial role in the regulation of prognosis and tumor immunology in cervical cancer, and its prognostic signature provides a strategy for risk stratification and immunotherapy evaluation.

A semi-parametric approach for time-dependent ROC curves with nonignorable missing biomarker

The main purpose of this paper is to survey the statistical inference for covariate-specific time-dependent receiver operating characteristic (ROC) curves with nonignorable missing continuous biomarker values. To construct time-dependent ROC curves, we consider a joint model which assumes that the failure time depends on the continuous biomarker and the covariates through a Cox proportional hazards model and that the continuous biomarker depends on the covariates through a semiparametric location model. Assuming a purely parametric model on the propensity score, we utilize instrumental variables to deal with the identifiable issue and estimate the unknown parameters of the propensity score by a simple and efficient method. In addition, when the propensity score is estimated, we develop HT and AIPW approaches to estimate our interested quantities. In the presence of nonignorable missing biomarker, our AIPW estimators of the interested quantities are still doubly robust when the true propensity score is a special parametric logistic model. At last, simulation studies are conducted to assess the performance of our proposed approaches, and a real data analysis is also carried out to illustrate its application.

Nutrition-inflammation marker enhances prognostic value to ECOG performance status in overweight or obese patients with cancer

BACKGROUND

Overweight or obese cancer patients are more likely to develop a proinflammatory status. The aim of this study was to investigate whether the nutrition-inflammation marker can provide additional prognostic information on top of well-established Eastern Cooperative Oncology Group performance status (ECOG-PS) in overweight or obese patients with cancer.

METHODS

A total of 1667 overweight or obese cancer patients were enrolled in this study. We assessed the prediction accuracy of 10 nutrition-inflammation markers by time-dependent receiver operating characteristic (ROC) and elucidated their association with overall survival by the Kaplan-Meier method and a Cox model.

RESULTS

In this analysis, the majority of patients had a good performance status (ECOG-PS score ≤1; 88.3%). Both the area under ROC curves and the C-index of the lymphocyte-C-reactive protein ratio (LCR) demonstrated that LCR was the most significant nutrition-inflammation marker correlated with survival. In patients with good ECOG-PS, a low LCR was significantly associated with poorer prognosisand enhanced the predictive ability of one-year mortality. For specific tumor types, a low LCR was an independent prognostic factor for lung cancer, upper gastrointestinal cancer, and colorectal cancer, and it tended to be a significant predictor for breast cancer. In addition, those patients with a combined low LCR and poorer ECOG-PS (ECOG-PS score >1) showed the worst prognosis.

CONCLUSION

The LCR is more strongly associated with overall survival than other nutrition-inflammation markers, and it is able to further detect patients with worse prognosis on top of ECOG-PS in overweight or obese patients with cancer.

Development and Validation of Prognostic Nomograms for Hepatocellular Carcinoma After Hepatectomy Based on Inflammatory Markers

Background

The value of lactate dehydrogenase (LDH) compared with other inflammation-based scores in predicting the outcomes of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients after curative resection remains unknown. This study aims to evaluate the predictive value of LDH and develop novel nomograms to predict postoperative recurrence and survival in these patients.

Methods

This study retrospectively collected 1560 patients with HBV-related HCC who underwent curative resection from four institutions in China. In total, 924 patients were recruited from our center and randomly divided into the training cohort (n = 616) and internal validation (n = 308) cohorts. Additionally, 636 patients were selected from three other centers as the external validation cohort. The C index of inflammation-based scores was calculated and compared in the training cohort. Novel models were developed according to multivariable Cox regression analysis in the training cohort and validated in the internal and external validation cohorts.

Results

LDH showed a higher C-index than other inflammation-based scores for recurrence survival (RFS, 0.60, 95% CI, 0.58-0.61) and overall survival (OS, 0.65, 95% CI, 0.63-0.68). The nomograms of RFS and OS were developed based on tumor diameter, macrovascular invasion, AFP, operative hemorrhage, tumor differentiation, tumor number and LDH and achieved a high C-index (0.78, 95% CI, 0.76-0.79 and 0.81, 95% CI, 0.79-0.83), which were remarkably higher than the C-indexes of the five conventional HCC staging systems (0.52-0.62 for RFS and 0.53-0.67 for OS). The nomograms were validated in the internal validation cohort (0.77 for RFS, 0.78 for OS) and external validation cohort (0.80 for RFS, 0.81 for OS) and performed well-fitted calibration curves.

Conclusion

The two nomograms based on inflammatory markers achieved optimal prediction for RFS and OS of patients with HBV-related HCC after hepatectomy.

Prognostic performance of different lymph node classification systems in young gastric cancer

Background

Accurate staging plays a pivotal role in cancer care. The lymph node (LN) ratio (LNR) and the log odds of positive LNs (LODDS) have been suggested as alternatives to the N staging since the TNM system has the risk of stage migration. The prognostic significance of LNR and LODDS in young patients with gastric cancer (GC) has not been reported. This study aims to investigate the correlations between LNR and LODDS and survival of young patients with GC, and compare the predictive performance of these LN staging methods.

Methods

GC patients before the age of 40 from 2004 to 2016 in the Surveillance, Epidemiology and End Results database were enrolled. The prognostic evaluation of the N factor, LNR and LODDS was compared using the time-dependent receiver operating characteristic (ROC) analysis, area under the curve (AUC), C-index and Akaike information criterion (AIC).

Results

Multivariate survival analysis identified that the LNR and LODDS were significantly independent prognostic indicators for overall survival (OS) in young patients with GC and in the subgroups comprised of patients with ≤15 LNs examined. The time-dependent ROC curves of the LNR and LODDS were continuously superior to that of the N factor in predicting OS during the observation period. And the AUCs revealed that the predictive accuracy of the LNR and LODDS was remarkably superior to the N factor at 1 and 3 years (P<0.05). The model incorporating LNR or LODDS had higher C-index and lower AIC when comparing to the model incorporating the N factor.

Conclusions

The LNR and LODDS improve accuracy of survival risk prediction in young patients with GC when comparing to the N factor. These two novel LN classification methods should be considered as alternatives to the N staging for the prognostic prediction of young patients with GC.

Prognostic significance and function of MCM10 in human hepatocellular carcinoma

Aim: To investigate the role of MCM10, a conserved replication factor, in hepatocellular carcinoma (HCC). Methods: We used data from 364 HCC patients in the Cancer Genome Atlas database and conducted in vitro experiments to confirm the role of MCM10. Results: High MCM10 expression correlated with poor HCC patient outcome and was an independent prognosticator for HCC. Time-dependent receiver operating characteristic curve analysis found that the sequential trend of MCM10 for survival was not inferior to that of the tumor node metastasis stage. The MCM10 model had a higher C-index than the non-MCM10 model, indicating that incorporating MCM10 into a multivariate model improves the model's prognostic accuracy for HCC. Genetic alterations of MCM10 prominently correlated with an unfavorable HCC outcome. Conclusion: Our findings strongly suggest using the MCM10 gene as a prognostic indicator in HCC.

Multi-omics landscape of circadian rhythm pathway alterations in Glioma

Circadian rhythm pathway was demonstrated pathological functions in glioma on single-gene level. We aim to depict the multi-omics landscape of circadian rhythm pathway alteration in glioma using bioinformatic analyses. Multi-omics data were obtained from “cBioPortal” database. Comparisons were done regarding clinical parameters, differential-expressed genes and functional annotations. A pathway index was generated using the expression data from TCGA and GTEx to quantify the general alteration level of the pathway with clinical association of circadian rhythm pathway index explored. A total of 30 genes were mapped on the circadian rhythm pathway. Genomic profile ofcircadian rhythm pathway genes exhibited distinct characteristics on multiple levels between lower grade glioma (LGG) and glioblastoma multiforme (GBM) patients. LGG patients presented significantly higher frequencies of multi-omics mutations, as well as significant clinical relevance, on single-gene level. Differential-expressed genes between LGG and GBM patients revealed different functions between subtypes that related to the alteration of circadian rhythm pathway. LGG have significantly higher pathway index than normal brain tissue, while GBM significantly lower than normal tissue (P < 0.01), indicating distinctly altered circadian pathway in LGG. Circadian rhythm pathway index correlated with the prognosis of LGG, but not GBM, patients, with higher score indicating better survival outcome (LGG: HR = 0.39, 95% CI: 0.26 − 0.59, P < 0.001). In conclusion, LGG have more multi-omics alterations of circadian rhythm pathway than GBM. Quantification of circadian rhythm pathway using pathway index demonstrated hyperactivated pathway status in LGG and correlated with the prognosis of LGG patients.

Development and Validation of a Model to Predict Long-Term Survival After Liver Transplantation

Patients are prioritized for liver transplantation (LT) under an "urgency-based" system using the Model for End-Stage Liver Disease score. This system focuses solely on waitlist mortality, without considerations of posttransplant morbidity, mortality, and health care use. We sought to develop and internally validate a continuous posttransplant risk score during 5-year and 10-year time horizons. This retrospective cohort study used national registry data of adult deceased donor LT (DDLT) recipients with ≥90 days of pretransplant waiting time from February 27, 2002 to December 31, 2018. We fit Cox regression models at 5 and 10 years to estimate beta coefficients for a risk score using manual variable selection and calculated the absolute predicted survival time. Among 21,103 adult DDLT recipients, 11 variables were selected for the final model. The area under the curves at 5 and 10 years were 0.63 (95% confidence interval [CI], 0.60-0.66) and 0.67 (95% CI, 0.64-0.70), respectively. The group with the highest ("best") scores had 5-year and 10-year survivals of 89.4% and 85.4%, respectively, compared with 45.9% and 22.2% for those with the lowest ("worst") scores. Our score was significantly better at predicting long-term survival compared with the existing scores. We developed and validated a risk score using nearly 17 years of data to prioritize patients with end-stage liver disease based on projected posttransplant survival. This score can serve as the building block by which the transplant field can change the entire approach to prioritizing patients to an approach that is based on considerations of maximizing benefits (ie, survival benefit-based allocation) rather than simply waitlist mortality.

Predicting survival after liver transplantation in patients with hepatocellular carcinoma using the LiTES-HCC score

BACKGROUND & AIMS

Liver transplant priority in the US and Europe follows the 'sickest-first' principle. However, for patients with hepatocellular carcinoma (HCC), priority is based on binary tumor criteria to expedite transplant for patients with 'acceptable' post-transplant outcomes. Newer risk scores developed to overcome limitations of these binary criteria are insufficient to be used for waitlist priority as they focus solely on HCC-related pre-transplant variables. We sought to develop a risk score to predict post-transplant survival for patients using HCC- and non-HCC-related variables.

METHODS

We performed a retrospective cohort study using national registry data on adult deceased-donor liver transplant (DDLT) recipients with HCC from 2/27/02-12/31/18. We fit Cox regression models focused on 5- and 10-year survival to estimate beta coefficients for a risk score using manual variable selection. We then calculated absolute predicted survival time and compared it to available risk scores.

RESULTS

Among 6,502 adult DDLT recipients with HCC, 11 variables were selected in the final model. The AUCs at 5- and 10-years were: 0.62, 95% CI 0.57-0.67 and 0.65, 95% CI 0.58-0.72, which was not statistically significantly different to the Metroticket and HALT-HCC scores. The LiTES-HCC score was able to discriminate patients based on post-transplant survival among those meeting Milan and UCSF criteria.

CONCLUSION

We developed and validated a risk score to predict post-transplant survival for patients with HCC. By including HCC- and non-HCC-related variables (e.g., age, chronic kidney disease), this score could allow transplant professionals to prioritize patients with HCC in terms of predicted survival. In the future, this score could be integrated into survival benefit-based models to lead to meaningful improvements in life-years at the population level.

LAY SUMMARY

We created a risk score to predict how long patients with liver cancer will live if they get a liver transplant. In the future, this could be used to decide which waitlisted patients should get the next transplant.

A preoperative prognostic nutritional index is a prognostic indicator in oral squamous cell carcinoma patients undergoing radical surgery

The purpose of this study was to investigate the prognostic value of prognostic nutritional index (PNI) in oral squamous cell carcinoma (OSCC) patients and to undertake a comparative evaluation of the prognostic value of comparing PNI, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) in terms of prognostic utility. A retrospective study was conducted involving 203 consecutive patients with OSCC who were treated with radical surgery with curative intent. The PNI and systemic inflammatory response were developed, and their prognostic utility was evaluated. Kaplan-Meier curve analysis and log-rank testing showed that PNI (P< 0.001), NLR (P=0.011), PLR (P=0.013), and LMR (P=0.014) were significantly associated with overall survival. Multivariate analysis identified PNI as an independent prognostic factor for OSCC patients (P=0.029). In time-dependent receiver operating characteristic curve analysis, PNI was continuously superior to that of NLR, PLR, and LMR. In conclusion, this study suggested that PNI offered an independent prognostic biomarker in OSCC patients undergoing radical surgery. However, this study was small and retrospective, thus further investigations are needed to clarify the utility of PNI for tailor-made treatments in clinical settings.

Covariates adjustment questioned conclusions of predictive analyses: an illustration with the Kidney Donor Risk Index

OBJECTIVES

We aimed to illustrate that considering covariates can lead to meaningful interpretation of the discriminative capacities of a prognostic marker. For this, we evaluated the ability of the Kidney Donor Risk Index (KDRI) to discriminate kidney graft failure risk.

STUDY DESIGN AND SETTING

From 4114 French patients, we estimated the adjusted area under the time-dependent ROC curve by standardizing the marker and weighting the observations. By weighting the contributions, we also studied the impact of KDRI-based transplantations on the patient and graft survival.

RESULTS

The covariate-adjusted AUC varied from 55% (95% confidence interval [CI]: 51-60%) for a prognostic up to 1 year post-transplantation to 56% (95% CI: 52-59%) up to 7 years. The Restricted Mean Survival Time (RMST) was 6.44 years for high-quality graft recipients (95% CI: 6.30-6.56) and would have been 6.31 years (95% CI: 6.13-6.46) if they had medium-quality transplants. The RMST was 5.10 years for low-quality graft recipients (95% CI: 4.90-5.31) and would have been 5.52 years (95% CI: 5.17-5.83) if they had medium-quality transplants.

CONCLUSION

We demonstrated that the KDRI discriminative capacities were mainly explained by the recipient characteristics. We also showed that counterfactual estimations, often used in causal studies, are also interesting in predictive studies, especially regarding the new available methods.

Single-nodule hepatitis B virus-associated hepatocellular carcinoma smaller than 3 cm: two phenotypes defined by cluster analysis and their association with the outcome of ablation as the first-line therapy

OBJECTIVES

Hepatocellular carcinoma (HCC) is a heterogeneous disease. This study aimed to identify the heterogeneity related to the prognosis of ablation in patients with single-nodule hepatitis B virus (HBV)-associated HCC ≤3 cm.

METHODS

A total of 359 patients with single-nodule HBV-associated HCC ≤3 cm treated with curative thermal ablation were retrospectively investigated. Hierarchical cluster analysis was applied to obtain more homogeneous patient clusters concerning demographic and physiological characteristics. Discriminant analysis was performed to identify the relatively important variables for cluster analysis. Multiple correspondence analysis (MCA) was used to clarify the relationship between clusters and categorical variables. Overall survival (OS) was compared among clusters using the Kaplan-Meier model.

RESULTS

A two-cluster model was identified. Cluster 1 (n = 85) showed a higher percentage of female and older patients, higher inflammation response (higher prognostic nutritional index [PNI] and Glasgow prognostic score [GPS]), worse liver function (higher albumin-bilirubin grade and Child-Pugh grade), and relatively poorer immune status (higher neutrophil-to-lymphocyte ratio [NLR]) than cluster 2 (n = 274). NLR and GPS were the two most influential variables for cluster analysis (p < .0001). Cluster 2 had a significantly better prognosis than cluster 1. MCA revealed a clear negative correlation between inflammation status and liver function. Compared with cluster 1, the hazard ratios for OS of cluster 2 were 0.47 and 0.52 before and after adjusting for age, respectively (p < .05).

CONCLUSIONS

This study identified two sub-phenotypes of patients with single-nodule HBV-associated HCC ≤3 cm and their association with the outcome of thermal ablation alone as the first-line therapy. Key points Thermal ablation alone as the first-line therapy is not suitable for all patients with single-nodule hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) ≤3 cm. Patients with single-nodule HBV-associated HCC ≤3 cm can be identified as two sub-phenotypes associated with the outcome of thermal ablation alone as the first-line therapy, based on key preoperative clinical characteristics, especially inflammatory response and immune status. Patients with single-nodule HBV-associated HCC ≤3 cm characterized by late-onset disease, worse liver function, poorer immune status, and higher inflammatory response (with higher inflammatory response being the most important factor) are not suitable for thermal ablation alone as the first-line therapy. In contrast, patients with single-nodule HBV-associated HCC ≤3 cm characterized by early-onset disease, better liver function, lower inflammatory response, and good immune status (with lower inflammatory response being the most important factor) are particularly suitable for thermal ablation alone. Implications for patient care In the treatment of patients with single-nodule HBV-associated HCC ≤3 cm, thermal ablation alone as the first-line therapy should be carefully considered after recognizing the key clinical characteristics, among which inflammatory response and immune status are the two most important factors involved in clinical heterogeneity, and inflammatory response is closely related to the prognosis of thermal ablation alone as the first-line therapy for these patients.

Recurrence Beyond the Milan Criteria of HBV-Related Single Hepatocellular Carcinoma of 2-3 cm: Comparison of Resection and Ablation

BACKGROUND

Comparison of patterns of early hepatocellular carcinoma (HCC) recurrence beyond the Milan criteria (HRBM) and identification of the independent risk factors of time to recurrence beyond the Milan criteria (TRBM) after resection or ablation can develop an optimal first-line treatment and provide more opportunities and waiting time for salvage transplantation.

METHODS

The patterns of HRBM after first-line resection or ablation in 384 patients with single-nodule HBV-associated HCC of 2-3 cm were retrospectively analyzed by one-to-one propensity score matching (PSM) between December 2008 and December 2017. The median TRBM between the resection group and the ablation group was estimated by Kaplan-Meier curves. The Cox regression analysis and binary logistic regression were used for the identification of the independent risk factors of TRBM and the occurrence of HRBM, respectively. The abilities of HRBM and the recurrence to predict overall survival (OS) were compared by the time-dependent receiver operating characteristic curves and estimated area under the curve.

RESULTS

Of 384 patients enrolled in our study, 260 (67.7%) received resection (resection group) and 124 (32.3%) underwent ablation (ablation group). The median TRBM in the resection group was significantly longer than that in the ablation group before PSM (median, not available vs. 101.4 months, P < 0.001) and after PSM (median, not available vs. 85.7 months, P < 0.001). Cox regression showed ablation, older age, CRP ≥1.81 mg/L, and PLT ≤80 × 10⁹/L were the independent risk factors of TRBM. Binary logistic regression also showed that ablation, CRP ≥1.81 mg/L, and PLT ≤80 × 10⁹/L were the independent risk factors of the occurrence of HRBM. The incidences of various phenotypes of HRBM were not significantly different between the two groups, but the incidence of HRBM at the first recurrence in the ablation group was significantly higher than that in the resection group (P < 0.05). Besides, compared with recurrence, HRBM was a better predictor of OS (P < 0.05).

CONCLUSIONS

Compared with ablation, resection should be considered as a more appropriate first-line option for patients with single-nodule HBV-associated HCC of 2-3 cm and a more promising bridge for liver transplantation in those patients.

Prognostic efficacy of preoperative mGPS, SIS and LCS in patients with gastric cancer

BACKGROUND

Systemic inflammation and interactions with host-tumor are currently identified as a hallmark of cancer. The purpose of this study was to assess the prognostic value of preoperative modified Glasgow Prognostic Score (mGPS), systemic inflammation score (SIS) and "lymphocyte C-reactive protein score" (LCS) in gastric cancer (GC) patients.

METHODS

358 GC patients were enrolled in this retrospective study. Kaplan-Meier method, multivariate Cox regression analysis, time-dependent receiver operating characteristics analysis (ROC), concordance index (C-index), and Akaike information criterion (AIC) were applied for assessments of the prognostic values.

RESULTS

Preoperative increased mGPS, SIS and LCS were all significantly linked with unfavorable overall survival using the Kaplan-Meier method (P < 0.001). Multivariate analysis proved that SIS was the only independent indicator among these three scoring systems. At the 4th-month point postoperatively, the time-dependent ROC curves of SIS and LCS crossed the curve of mGPS and were consistently superior to that of mGPS thereafter. The model incorporating SIS had higher C-index and smaller AIC than did the model without SIS or the models with mGPS or LCS.

CONCLUSION

Preoperative SIS exceeded both the mGPS and LCS and was the most clinically promising and feasible prognostic scoring system for GC patients.

Hepatocellular Carcinoma Within the Milan Criteria: A Novel Inflammation-Based Nomogram System to Assess the Outcomes of Ablation

Objectives

Few studies based on pretreatment inflammation-based scores focused on assessing the prognosis of hepatocellular carcinoma (HCC) patients within the Milan Criteria after ablation. This study aimed to construct a nomogram based on a novel inflammation-based score for those patients.

Methods

A total of 635 HCC patients within the Milan Criteria after ablation meeting the inclusion and exclusion criteria were included in the study. The novel inflammation-based score-Albumin-Platelet Score (APS)-was constructed by Cox proportional-hazards modeling. The nomogram based on APS was constructed by multivariate analysis and the "rms" R package. The performance of the APS and the nomogram were assessed by time-dependent receiver operating characteristic and the concordance index (C-index).

Results

The APS was an integrated indicator based on peripheral albumin level and platelet counts, which was significantly superior to other inflammation-based scores (neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, Prognostic Nutritional Index, modified Glasgow Prognostic Score, Glasgow Prognostic Score, Prognostic Index, and C-reactive protein/albumin ratio) in predicting the long-term prognosis of those patients undergoing ablation (P < 0.05). An easy-to-use nomogram based on three pretreatment clinical variables (i.e., the APS, tumor size, and age) was constructed and further improved significantly the performance in predicting the prognosis in patients within the Milan Criteria after ablation (P < 0.05). The C-index of nomogram for overall survival was 0.72 (95% CI 0.66, 0.77). The calibration plots with 1000 cycles of bootstrapping were well matched with the idealized 45° line.

Conclusion

The APS was a better inflammation-based prognostic system than others. Also, the nomogram based on the APS improved the performance of predicting the prognosis of HCC patients within the Milan Criteria after ablation.

Complete blood count-based inflammatory score (CBCS) is a novel prognostic marker for gastric cancer patients after curative resection

Background

We sought to investigate the prognostic value of complete blood count (CBC)-based biomarkers for patients with resectable gastric cancer (GC).

Methods

Patients with GC who underwent primary surgical resection between December 2008 and December 2013 were included. The estimated area under the curve (AUC) and multivariate Cox regression models were used to identify the best CBC-based biomarker. Time-dependent receiver operating characteristic (t-ROC) curve analysis was used to predict overall survival and compare the prognostic impact.

Results

In the 1810 patients analyzed, the median follow-up period was 51.0 months (range 1–101 months). Based on multivariate analysis, the lymphocyte-monocyte ratio (LMR) and hemoglobin (Hb) level were independent prognostic factors (both P < 0.05). Based on the LMR and Hb level, we established the CBC-based inflammatory score (CBCS). A higher CBCS was associated with older age, female sex, higher American Society of Anesthesiologists (ASA) score, proximal tumor location, larger tumor size, later stage and vascular involvement (all P < 0.05). Univariate analyses showed that a higher CBCS was also associated with worse overall survival (OS), which was consistent in each stage (all P < 0.05). Multivariate analysis revealed that the CBCS was a significant independent biomarker (P < 0.05). The AUC for the CBCS (0.627) was significantly higher than the AUCs for the LMR (0.573) and Hb level (0.605) (both P < 0.05). Furthermore, the t-ROC curve of the CBCS was superior to that of the prognostic nutritional index (PNI), systemic immune-inflammation index (SII), modified Glasgow prognostic score (mGPS) and C-reactive protein/albumin ratio (CRP/Alb) throughout the observation period.

Conclusion

The preoperative LMR and Hb level were optimal CBC-based biomarkers for predicting OS in GC patients after curative resection. Based on the LMR and Hb, we developed a novel and easily obtainable prognostic score called the CBCS, which may improve the prediction of clinical outcomes.

Comparison of the prognostic value of inflammation-based scores in early recurrent hepatocellular carcinoma after hepatectomy

BACKGROUND & AIMS

Inflammation-based prognostic scores, such as the Glasgow Prognostic Score (GPS), modified Glasgow Prognostic Score (mGPS), Prognostic Index (PI), Prognostic Nutritional Index (PNI), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and systemic immune-inflammation index (SII), are correlated with the survival of hepatocellular carcinoma (HCC) patients, while remain unclear for recurrent HCC. This study aimed to compare the prognostic value of inflammation-based prognostic scores for post-recurrence survival (PRS) in patients with early recurrent HCC (ErHCC, within 2 years after hepatectomy).

METHODS

A total of 580 patients with ErHCC were enrolled retrospectively. The association between the independent baseline and the time-dependent variables and PRS was evaluated by cox regression. The prediction accuracy of the inflammation-based prognostic scores was assessed by time-dependent receiver operating characteristic (ROC) and Harrell's concordance index (C-index) analyses.

RESULTS

The GPS, mGPS, PI, PNI, NLR, PLR, LMR and SII were all related to the PRS of ErHCC patients, while only the SII (P < .001) remained an independent predictor for PRS in multivariate analysis (hazard ratio: 1.92, 95% confidence interval: 1.33-2.79). Both the C-index of the SII (0.65) and the areas under the ROC curves showed that the SII score was superior to the other inflammation-based prognostic scores for predicting the PRS of ErHCC patients.

CONCLUSIONS

The SII is a useful prognostic indicator for PRS in patients with ErHCC after hepatectomy and is superior to the other inflammation-based prognostic scores in terms of prognostic ability.

Development and validation of a staging system for gastric adenocarcinoma after neoadjuvant chemotherapy and gastrectomy with D2 lymphadenectomy

BACKGROUND

Neoadjuvant chemotherapy followed by gastrectomy with D2 lymphadenectomy is commonly used for patients with locally advanced gastric adenocarcinoma. The eighth AJCC ypTNM staging system was validated based on patients undergoing more limited lymphadenectomy (less than D2). The aim of this study was to develop a system for accurate staging of patients with locally advanced gastric adenocarcinoma who receive neoadjuvant chemotherapy followed by gastrectomy with D2 lymphadenectomy.

METHODS

A modified system of ypTNM was developed, based on overall survival (OS) of patients receiving neoadjuvant chemotherapy followed by gastrectomy with D2 lymphadenectomy at Memorial Sloan Kettering Cancer Center, and validated using data from an international cohort of patients who had similar treatment.

RESULTS

Of 325 patients in the derivation cohort, 33 (10·2 per cent) had ypT0 N0/+ tumours, which are not classifiable under the AJCC system. The 5-year OS rate for modified ypTNM stages I, II, IIIA and IIIB was 89, 71, 42·3 and 10 per cent respectively, compared with 82, 65·2 and 24·1 for AJCC stages I, II and III respectively. The concordance index (0·730 versus 0·709), estimated area under the curve (0·765 versus 0·740) and time-dependent receiver operating characteristic (ROC) curve throughout the observation period were all superior for modified ypTNM staging. For the validation cohort of 186 patients, the modified system was again better at separating patients into prognostic groups for OS.

CONCLUSION

The modified ypTNM staging system improves the accuracy of OS prediction for patients treated with neoadjuvant chemotherapy followed by gastrectomy with D2 lymphadenectomy.

Prognostic importance of the preoperative modified systemic inflammation score for patients with gastric cancer

BACKGROUND

The systemic inflammation score (SIS), based on preoperative serum albumin (Alb) level and lymphocyte-to-monocyte ratio (LMR), has been shown to be a novel prognostic score for some tumors. We investigate the prognostic value of the SIS in patients with resectable gastric cancer (GC).

METHODS

Patients with GC who underwent curative resection between December 2008 and December 2013 were included. Time-dependent receiver operating characteristics analysis (t-ROC), concordance index (C-index) and AUC were used to compare the prognostic impact.

RESULTS

Totally, 1786 patients with resectable GC were included in the study. By multivariate analysis, the SIS was not an independent prognostic factor. However, the normal Alb level (≥ 40 g/l) and LMR ≥ 3.4 both remained independent protective factors for GC (both P < 0.05). Due to the similar survival of patients with LMR ≥ 3.4 and LMR < 3.4 in the normal Alb group, we combined the two subgroups to establish the modified SIS (mSIS). Multivariate analysis revealed that the mSIS was the only significant independent biomarker (P < 0.05). The t-ROC curve and C-index for the mSIS were superior to those of the SIS throughout the observation period. Furthermore, the AUC of the mSIS was significantly greater than that of the SIS at 3 and 5 years after operation (both P < 0.05).

CONCLUSION

The preoperative mSIS is a novel, simple and useful prognostic factor for postoperative survival in patients with GC and can be used as a part of the preoperative risk stratification process to improve the prediction of clinical outcomes.

Comparison of Preoperative Inflammation-based Prognostic Scores in Patients With Colorectal Cancer

OBJECTIVE

To evaluate the prognostic impact of the systemic inflammation score (SIS) in colorectal cancer (CRC) patients in comparison with a conventional inflammation-based score, the modified Glasgow Prognostic Score (mGPS).

SUMMARY BACKGROUND DATA

The SIS, which is calculated based on the preoperative serum albumin level and lymphocyte-to-monocyte ratio, is a reported prognostic marker in clear-cell renal cell carcinoma. However, the utility of the SIS in CRC remains unclear.

METHODS

The study involved 727 CRC patients who underwent curative resection between September 2005 and December 2011. The prognostic impact of SIS and mGPS was evaluated using survival analyses. The prognostic impact of each score was compared visually by means of time-dependent receiver operating characteristics analysis.

RESULTS

The median age of the patients was 67 (interquartile range: 58-75) years. The TNM stage distribution was stage I, 29.8%; stage II, 33.6%; stage III, 30.3%; and stage IV, 6.3%. The median follow-up period was 5.61 years (interquartile range: 4.24-7.06). Multivariate analysis revealed that an increased SIS and mGPS were independent prognostic factors (SIS: P = 0.018; mGPS: P = 0.005, respectively). The time-dependent receiver operating characteristics curve of the SIS was superior to that of the mGPS throughout the observation period. The estimated area under the curve (AUC) of the SIS was significantly higher than that of the mGPS (7-yr survival: SIS 0.673, mGPS 0.605, P = 0.030).

CONCLUSIONS

The SIS is a novel prognostic factor in CRC patients. Additionally, the SIS is an alternative inflammation-based biomarker, which may improve the prediction of clinical outcomes.

Is the 8th Edition of the AJCC TNM Staging System Sufficiently Reasonable for All Patients with Noncardia Gastric Cancer? A 12,549-Patient International Database Study

BACKGROUND

The aim of this work is to compare the prognostic ability between the 7th and 8th editions of the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) classification for gastric cancer (GC).

METHODS

A total of 10,194 noncardia GC patients were identified from the Surveillance, Epidemiology, and End Results database from 1988 to 2008. Concordance index (C-index), bayesian information criterion (BIC), and time-dependent receiver operating characteristic (t-ROC) analyses were used. External validation was performed using a dataset (n = 2355) derived from Fujian Medical University Union Hospital.

RESULTS

Overall survival for all five AJCC N categories differed significantly when patients were subgrouped into ≤ 15 versus >15 examined lymph nodes (eLNs). The prognostic ability of the 8th edition (C-index 0.716) was not improved over the 7th edition (C-index 0.716). Subgroup analysis showed superior performance of the 8th over the 7th edition in patients with > 15 eLNs (C-index 0.742 vs. 0.735); however, the two editions showed similar performance for patients with ≤ 15 eLNs (C-index 0.713 vs. 0.713). The BIC and t-ROC analyses were consistent. To better predict the prognosis of patients with ≤ 15 eLNs, we established a novel prognostic model based on independent prognostic factors (C-index 0.735). BIC analysis showed that this new model was better than the 7th and 8th editions. Similar results were obtained from the validation set.

CONCLUSIONS

The 8th edition of the AJCC TNM classification shows better prognostic ability than the 7th edition in noncardia GC patients with > 15 eLNs, but no improvement was found in patients with ≤ 15 eLNs; therefore, a novel prognostic model is proposed.

Standardized and weighted time-dependent receiver operating characteristic curves to evaluate the intrinsic prognostic capacities of a marker by taking into account confounding factors

Time-dependent receiver operating characteristic curves allow to evaluate the capacity of a marker to discriminate between subjects who experience the event up to a given prognostic time from those who are free of this event. In this article, we propose an inverse probability weighting estimator of a standardized and weighted time-dependent receiver operating characteristic curve. This estimator provides a measure of the prognostic capacities by taking into account potential confounding factors. We illustrate the robustness of the estimator by a simulation-based study and its usefulness by two applications in kidney transplantation.

Classification of biodegradable materials using QSAR modelling with uncertainty estimation

The ability to determine the biodegradability of chemicals without resorting to expensive tests is ecologically and economically desirable. Models based on quantitative structure-activity relations (QSAR) provide some promise in this direction. However, QSAR models in the literature rarely provide uncertainty estimates in more detail than aggregated statistics such as the sensitivity and specificity of the model's predictions. Almost never is there a means of assessing the uncertainty in an individual prediction. Without an uncertainty estimate, it is impossible to assess the trustworthiness of any particular prediction, which leaves the model with a low utility for regulatory purposes. In the present work, a QSAR model with uncertainty estimates is used to predict biodegradability for a set of substances from a publicly available data set. Separation was performed using a partial least squares discriminant analysis model, and the uncertainty was estimated using bootstrapping. The uncertainty prediction allows for confidence intervals to be assigned to any of the model's predictions, allowing for a more complete assessment of the model than would be possible through a traditional statistical analysis. The results presented here are broadly applicable to other areas of modelling as well, because the calculation of the uncertainty will clearly demonstrate where additional tests are needed.

Detection of Serum Interleukin-6/10/18 Levels in Sepsis and Its Clinical Significance

OBJECTIVE

To explore the clinical significance of serum levels of IL-6/10/18 in sepsis.

METHODS

Sixty-six patients with sepsis were selected to be the case group. Additionally, 42 healthy adults were selected to be the control group. ELISA was used to measure the serum levels of IL-6/10/18, and ROC was utilized to evaluate the diagnostic values of IL-6/10/18 in sepsis.

RESULTS

The heart rate, respiratory rate, WBC count and APACHE II score in the sepsis group were significantly higher than those in the control group, and these indexes were increased in turn in the mild sepsis group, severe sepsis group, and septic shock group (all P < 0.05 after correction). The serum IL-6/18 levels in sepsis patients were significantly higher than those in the control group, and both of the levels were increased in turn in the mild sepsis group, severe sepsis group, and septic shock group (both P < 0.05). However, no significant difference was found in serum IL-10 level between groups (P > 0.05). The cut-off points of IL-6 and IL-18 were 109.19 pg/ml (sensitivity: 94.4%; specificity: 83.3%) and 116.01 pg/ml (sensitivity: 77.8%; specificity: 83.3%), respectively. Serum IL-6 levels were positively correlated with the APACHE II score and heart rate (both P < 0.001).

CONCLUSION

Serum levels of IL-6/8 are up-regulated in sepsis patients. Additionally, IL-6 has a greater sensitivity than IL-18. Serum IL-6 levels were positively correlated with the APACHE II score and heart rate, indicating that IL-6 could be used as a potential biomarker for sepsis.