Background : Lymphocytes were reported to play a significant part in host anticancer immune responses and influence tumour prognosis. Few studies have focused on the prognostic values of aspartate aminotransferase (AST) to lymphocyte ratio (ALRI), aspartate aminotransferase to platelet count ratio index (APRI) and systemic immune-inflammation index (SII) in hepatocellular carcinoma (HCC) treated with palliative treatments. Methods : Five hundred and ninety-eight HCC patients treated with palliative therapies were retrospectively analysed. We randomly assigned patients into the training cohort (429 patients) and the validation cohort I (169 patients). Receiver operating characteristic (ROC) curves were used to identify the best cut-off values for the ALRI, APRI and SII in the training cohort and the values were further validated in the validation cohort I. Correlations between ALRI and other clinicopathological factors were also analysed. A prognostic nomogram including ALRI was established. We validated the prognostic value of the ALRI, SII and APRI with two independent cohorts, the validation cohort II of 82 HCC patients treated with TACE and the validation cohort III of 150 HCC patients treated with curative resection. In the training cohort and all the validation cohorts, univariate analyses by the method of Kaplan-Meier and multivariate analysis by Cox proportional hazards regression model were carried out to identify the independent prognostic factors. Results : The threshold values of ALRI, APRI and SII were 86.3, 1.37 and 376.4 respectively identified by ROC curve analysis in the training cohort. Correlation analysis showed that ALRI>86.3 was greatly associated with higher rates of Child-Pugh B&C, portal vein tumor thrombosis (PVTT) and ascites ( P < 0.05). Correspondingly, ALRI level of HCC patients with Child-Pugh B&C, PVTT and ascites was evidently higher than that of HCC patients with Child-Pugh A, without PVTT and without ascites ( P < 0.001). In the training cohort and the validation cohort I, II, III, the OS of patients with ALRI >86.3 was obviously shorter than patients with ALRI ≤86.3 ( P < 0.001). We identified ALRI as an independent prognostic factor by univariate and multivariate analyses both in training Cohort (HR=1.481, P= 0.004), validation cohort I (HR=1.511, P= 0.032), validation cohort II (HR=3.166, P= 0.005) and validation cohort III (HR=3.921, P= 0.010). The SII was identified as an independent prognostic factor in training cohort (HR=1.356, P= 0.020) and the validation cohort II (HR=2.678, P= 0.002). The prognostic nomogram including ALRI was the best in predicting 3-month, 6-month, 1-year, 2-year survival And OS among TNM, ALRI, ALRI-TNM and nomogram. Conclusions : The ALRI was a novel indep...

Medical devices generate huge amounts of continuous time series data. However, missing values commonly found in these data can prevent us from directly using analytic methods such as sample entropy to reveal the information contained in these data. To minimize the influence of missing points on the calculation of sample entropy, we propose a new method to handle missing values in continuous time series data. We use both experimental and simulated datasets to compare the performance (in percentage error) of our proposed method with three currently used methods: skipping the missing values, linear interpolation, and bootstrapping. Unlike the methods that involve modifying the input data, our method modifies the calculation process. This keeps the data unchanged which is less intrusive to the structure of the data. The results demonstrate that our method has a consistent lower average percentage error than other three commonly used methods in multiple common physiological signals. For missing values in common physiological signal type, different data size and generating mechanism, our method can more accurately extract the information contained in continuously monitored data than traditional methods. So it may serve as an effective tool for handling missing values and may have broad utility in analyzing sample entropy for common physiological signals. This could help develop new tools for disease diagnosis and evaluation of treatment effects.

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The aim of the present study was to evaluate the ability of seven staging systems to predict 3- and 6-month and cumulative survival rates of patients with advanced hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). Data were collected from 220 patients with HBV-associated HCC who did not receive any standard anticancer treatment. Participants were patients at The Third Affiliated Hospital of Sun Yat-sen University from September 2008 to June 2010. The participants were classified according to the Chinese University Prognostic Index (CUPI), the Cancer of the Liver Italian Program (CLIP), Japan Integrated Staging (JIS), China Integrated Score (CIS) systems, Barcelona Clinic Liver Cancer (BCLC), Okuda and tumor-node-metastasis (TNM) staging systems at the time of diagnosis and during patient follow-up. The sensitivity and specificity of the predictive value of each staging system for 3- and 6-month mortality were analyzed by relative operating characteristic (ROC) curve analysis with a non-parametric test being used to compare the area under curve (AUC) of the ROC curves. In addition, log-rank tests and Kaplan-Meier estimator survival curves were applied to compare the overall survival rates of the patients with HCC defined as advanced using the various staging systems, and the Akaike information criterion (AIC) and likelihood ratio tests (LRTs) were used to evaluate the predictive value for overall survival in patients with advanced HCC. Using univariate and multivariate Cox's model analyses, the factors predictive of survival were also identified. A total of 220 patients with HBV-associated HCC were analyzed. Independent prognostic factors identified by multivariate analyses included tumor size, α-fetoprotein levels, blood urea nitrogen levels, the presence or absence of portal vein thrombus, Child-Pugh score and neutrophil count. When predicting 3-month survival, the AUCs of CLIP, CIS, CUPI, Okuda, TNM, JIS and BCLC were 0.806, 0.772, 0.751, 0.731, 0.643, 0.754 and 0.622, respectively. When predicting 6-month survival, the AUCs of CLIP, CIS, CUPI, Okuda, TNM, JIS and BCLC were 0.828, 0.729, 0.717, 0.692, 0.664, 0.746 and 0.575, respectively. For 3-month mortality, the prognostic value of CLIP ranked highest, followed by CIS; for 6-month mortality, the prognostic value of CLIP also ranked highest, followed by JIS. No significant difference between the AUCs of CLIP and CIS (P>0.05) in their predictive value for 3-month mortality was observed. The AUC of CLIP was significantly higher compared with that of the other staging systems (P<0.05) for predicting 6-month mortality. The χ2 values from the LRTs of CLIP, CIS, CUPI, Okuda, TNM, JIS and BCLC were 75.6, 48.4, 46.7, 36.0, 21.0, 46.8 and 7.24, respectively. The AIC values of CLIP, CIS, CUPI, Okuda, TNM, JIS and BCLC were 1601.5, 1632.3, 1629.9, 1641.1, 1654.8, 1627.4 and 1671.1, respectively. CLIP exhibited the highest χ2 value and lowest AIC value, indicating that CLIP has the highest predictive value of cumulative survival rate. In the selected pat...

Background & aims:Nutritional interventions for malnutrition in cancer patients can be helpful. However, concise intervention recommendations remain controversial. Thus, the aim of this study was to report on a nutrition intervention conducted by a multidisciplinary team of specialist nurses and to explore the effect of nutritional intervention on cancer patients.Methods:This prospective clinical trial study enrolled 110 colorectal cancer patients undergoing chemotherapy. The patients were evaluated upon admission using the 2002 Nutritional Risk Screening system (NRS-2002). The patients were randomly divided into intervention and control groups including 55 patients each. Patients in the control group were administered a normal diet, while those in the intervention group received individual recipes developed by a team of professional nurses, clinical doctors, dietitian, family caregivers, and the patients themselves. Patient weight and serum albumin and prealbumin levels were compared between the 2 groups at different time points.Results:There was a significant difference in patient weight and serum albumin and prealbumin levels before and after nutrition intervention in the intervention group (P < .05). In the control group, weight did not change during ordinary diet guidance. Serum albumin level was slightly improved after 12 cycles of chemotherapy, similar to the prealbumin results. There were statistically significant differences in serum albumin and prealbumin levels between the intervention and control groups after nutrition intervention (P < .05). However, there was no statistically significant difference in weight between the groups after nutrition intervention (P > .05).Conclusion:A multidisciplinary team approach for nutrition intervention conducted by specialist nurses improved prealbumin levels in colorectal cancer patients undergoing chemotherapy, with no weight change.