Mean corpuscular hemoglobin concentration correlates with prognosis of resected hepatocellular carcinoma

Bioconjugate based on cisplatin and bacterial exopolysaccharide with reduced side effects: A novel proposal for cancer treatment

BACKGROUND

In the search for alternatives that attenuate the toxicity associated to oncologic treatment with cisplatin (CDDP) and considering the potential health-beneficial properties of exopolysaccharides (EPS) produced by lactic acid bacteria, it was aimed on this study to evaluate the cytotoxic, toxicologic and antitumoral efficacy of a bioconjugate based on CDDP and EPS, on the experimental tumor of sarcoma 180.

METHODS

After the synthesis of the cis-[Pt(NH3)2(Cl)2] complex and of the conjugate containing Lactobacillus fermentum exopolysaccharide was tested both in vitro and in vivo for evaluating the acute toxicity.

RESULTS

The antitumoral study was performed using mice transplanted with sarcoma 180. The bioconjugate showed low to medium cytotoxicity for the cell lines tested, as well moderated acute toxicity. After determining the LD50, the following experimental groups were established for the antitumor assay: Control (NaCl 0,9%), CDDP (1 mg/kg), EPS and bioconjugate composition (200 mg/kg). The bioconjugate promoted a 38% regression in tumor mass when compared to the control, and a regression of 41% when compared to CDDP. Liver histopathological analysis revealed discrete alterations in animals treated with (CDDP + EPS) when compared to control. The bioconjugate also minimized changes in the renal parenchyma resulting from the tumor.

CONCLUSION

Our results indicate that when CDDP is associated with EPS, this composition was more biocompatible, showing itself as a potent chemotherapeutic agent and lower tissue toxicity.

Risk Models for Predicting the Recurrence and Survival in Patients With Hepatocellular Carcinoma Undergoing Radio-Frequency Ablation

Background

Hepatocellular carcinoma (HCC) patients have a poor prognosis after radio-frequency ablation (RFA), and investigating the risk factors affecting RFA and establishing predictive models are important for improving the prognosis of HCC patients.

Methods

Patients with HCC undergoing RFA in Shenzhen People's Hospital between January 2011 and December 2021 were included in this study. Using the screened independent influences on recurrence and survival, predictive models were constructed and validated, and the predictive models were then used to classify patients into different risk categories and assess the prognosis of different categories.

Results

Cox regression model indicated that cirrhosis (hazard ratio [HR] = 1.65), alpha-fetoprotein (AFP) ⩾400 ng/mL (HR = 2.03), tumor number (multiple) (HR = 2.11), tumor diameter ⩾20 mm (HR = 2.30), and platelets (PLT) ⩾ 244 (109/L) (HR = 2.37) were independent influences for recurrence of patients after RFA. On the contrary, AFP ⩾400 ng/mL (HR = 2.48), tumor number (multiple) (HR = 2.52), tumor diameter ⩾20 mm (HR = 2.25), PLT ⩾244 (109/L) (HR = 2.36), and hemoglobin (HGB) ⩾120 (g/L) (HR = 0.34) were regarded as independent influences for survival. The concordance index (C-index) of the nomograms for predicting disease-free survival (DFS) and overall survival (OS) was 0.727 (95% confidence interval [CI] = 0.770-0.684) and 0.770 (95% CI = 0.821-7.190), respectively. The prognostic performance of the nomograms was significantly better than other staging systems by analysis of the time-dependent C-index and decision curves. Each patient was scored using nomograms and influencing factors, and patients were categorized into low-, intermediate-, and high-risk groups based on their scores. In the Kaplan-Meier survival curve, DFS and OS were significantly better in the low-risk group than in the intermediate- and high-risk groups.

Conclusions

The 2 prediction models created in this work can effectively predict the recurrence and survival rates of HCC patients following RFA.

Platelet count and MCHC as independent prognostic markers for feline mammary carcinomas

Mammary neoplasms are common in felines species and represent a significant disease for its unfavorable prognosis. Changes in the blood count and serum biochemical profile of these patients have potential as non-invasive prognostic markers prior to mastectomy, however, they are poorly described in literature. In this study univariate and multivariate analyses were performed using these factors to determine the effect of each parameter on the one-year survival time after the surgical procedure in these animals. The median overall survival (OS) and the disease-free survival (DFS) were 365 and 242 days, respectively. In univariate analysis, values within the reference range of monocyte, platelet and creatinine counts were identified as significant prognostic factors for OS and only creatinine was significant for DFS (P < 0.05). In the multivariate analysis, platelets and mean corpuscular hemoglobin concentration (MCHC) remained independent prognostic factors for OS. The results presented suggest that monocytes, platelets and creatinine may be important non-invasive pre-surgical prognostic markers, and that platelet count and MCHC are independent prognostic markers for feline mammary carcinomas (FMC). The correlation between such alterations is of important relevance for veterinary oncology, and prospective studies are needed to validate their clinical use and that platelet count and MCHC are independent prognostic markers for FMC. The results found in this study can also be studied in human medicine, regarding blood markers in human breast cancer (HBC).

Development and Validation of a nomogram for forecasting survival of alcohol related hepatocellular carcinoma patients

BACKGROUND

With the increasing incidence and prevalence of alcoholic liver disease, alcohol-related hepatocellular carcinoma has become a serious public health problem worthy of attention in China. However, there is currently no prognostic prediction model for alcohol-related hepatocellular carcinoma.

METHODS

The retrospective analysis research of alcohol related hepatocellular carcinoma patients was conducted from January 2010 to December 2014. Independent prognostic factors of alcohol related hepatocellular carcinoma were identified by Lasso regression and multivariate COX proportional model analysis, and the nomogram model was constructed. The reliability and accuracy of the model were assessed using the concordance index(C-Index), receiver operating characteristic (ROC) curve and calibration curve. Evaluate the clinical benefit and application value of the model through clinical decision curve analysis (DCA). The prognosis was assessed by the Kaplan-Meier (KM) survival curve.

RESULTS

In sum, 383 patients were included in our study. Patients were stochastically assigned to training cohort (n=271) and validation cohort (n=112) according to 7:3 ratio. The predictors included in the nomogram were splenectomy, platelet count (PLT), creatinine (CRE), Prealbumin (PA), mean erythrocyte hemoglobin concentration (MCHC), red blood cell distribution width (RDW) and TNM. Our nomogram demonstrated excellent discriminatory power (C-index) and good calibration at 1-year, 3-year and 5- year overall survival (OS). Compared to TNM and Child-Pugh model, the nomogram had better discriminative ability and higher accuracy. DCA showed high clinical benefit and application value of the model.

CONCLUSION

The nomogram model we established can precisely forcasting the prognosis of alcohol related hepatocellular carcinoma patients, which would be helpful for the early warning of alcohol related hepatocellular carcinoma and predict prognosis in patients with alcoholic hepatocellular carcinoma.

A Simple Nomogram for Predicting Osteoarthritis Severity in Patients with Knee Osteoarthritis

Objective

To explore the influencing factors of knee osteoarthritis (KOA) severity and establish a KOA nomogram model.

Methods

Inpatient data collected in the Department of Joint Surgery, Chengde Medical University Affiliated Hospital from January 2020 to January 2022 were used as the training cohort. Patients with knee osteoarthritis who were admitted to the Third Hospital of Hebei Medical University from February 2022 to May 2022 were taken as the external validation group of the model. In the training group, the least absolute shrinkage and selection operator (LASSO) method was used to screen the factors of KOA severity to determine the best prediction index. Then, after combining the significant factors from the LASSO and multivariate logistic regressions, a prediction model was established. All potential prediction factors were included in the KOA severity prediction model, and the corresponding nomogram was drawn. The consistency index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), GiViTi calibration band, net classification improvement (NRI) index, and integrated discrimination improvement (IDI) index evaluation of a model predicted KOA severity. Decision curve analysis (DCA) and clinical influence curves were used to study the model's potential clinical value. The validation group also used the above evaluation indexes to measure the diagnostic efficiency of the model. Spearman correlation was used to investigate the relationship between nomogram-related markers and osteoarthritis severity.

Results

The total sample included 572 patients with knee osteoarthritis, including 400 patients in the training cohort and 172 patients in the validation cohort. The nomogram's predictive factors were age, pulse, absolute value of lymphocytes, mean corpuscular haemoglobin concentration (MCHC), and blood urea nitrogen (BUN). The C-index and AUC of the model were 0.802. The GiViTi calibration band (P = 0.065), NRI (0.091), and IDI (0.033) showed that the modified model can distinguish between severe KOA and nonsevere KOA. DCA showed that the KOA severity nomogram has clinical application value with threshold probabilities between 0.01 and 0.78. The external verification results also show the stability and diagnosis of the model. Age, pulse, MCHC, and BUN are correlated with osteoarthritis severity.

Conclusions

A nomogram model for predicting KOA severity was established for the first time that can visually identify patients with severe KOA and is novel for indirectly evaluating KOA severity by nonimaging means.

Type O blood, the MCHC, and the reticulocyte count impact the early recurrence of primary warm-antibody autoimmune hemolytic anemia in children: A retrospective cohort analysis

OBJECTIVE

Primary warm-antibody autoimmune hemolytic anemia (w-AIHA) is prone to recurrence in children. In this study, we aimed to identify risk indicators for the early recurrence of primary w-AIHA and construct an effective recurrence risk assessment model.

METHODS

This was a retrospective cohort study. The clinical data of patients hospitalized with primary w-AIHA in the Department of Hematology and Oncology, Children's Hospital of Chongqing Medical University, between 1 January 2018 and 30 September 2021, were collected at the initial diagnosis. Univariate and multivariate logistic regression analyses were used to determine risk indicators for the early recurrence of primary w-AIHA in children, and ROC curve and Kaplan-Meier survival analyses were used for verification. Finally, a risk assessment model for early recurrence in children with primary w-AIHA was constructed using Cox regression and visualized using a nomogram. The model was also verified internally and externally.

RESULTS

This study included 62 children with primary w-AIHA. Of which, 18 experienced recurrence 1 year after the initial diagnosis. The univariate and multivariate logistic regression analyses showed that type O blood and the reticulocyte count (Ret) were risk indicators for the early recurrence of pediatric primary w-AIHA (P = 0.009, 0.047, respectively). The mean corpuscular hemoglobin concentration (MCHC) is a protective factor (P = 0.040). According to the ROC curve and Kaplan-Meier survival analyses, children with primary w-AIHA whose blood type was O or had an MCHC of <313.5 pg/fL or a Ret of ≥0.161×10¹²/L had a higher risk of early recurrence (HR = 2.640, 4.430 and 4.450, respectively, and P = 0.040, 0.015 and 0.018, respectively). The blood types (O), MCHCs, and Rets of 56 patients were incorporated into the Cox regression model, and the recurrence risk assessment model for children with primary w-AIHA was successfully constructed and visualized using a nomogram. The calibration curves and decision-curve analysis (DCA) suggested that the risk model has clinical applicability and effectiveness.

CONCLUSION

Children with type O blood and an MCHC value of <313.5 pg/fL or a Ret value of ≥0.161×10¹²/L have a higher risk of early recurrence. The risk assessment model for the early recurrence of pediatric primary w-AIHA constructed in this study has good clinical applicability and effectiveness.