The ROC of Cox proportional hazards cure models with application in cancer studies

Exploration of TCM syndrome types of the material basis and risk prediction of Wilson disease liver fibrosis based on 1H NMR metabolomics

Wilson disease (WD) is an autosomal recessive disorder characterized by abnormal copper metabolism. The accumulation of copper in the liver can progress to liver fibrosis and, ultimately, cirrhosis, which is a primary cause of death in WD patients. Metabonomic technology offers an effective approach to investigate the traditional Chinese medicine (TCM) syndrome types of WD-related liver fibrosis by monitoring the alterations in small molecule metabolites within the body. In this study, we employed 1H-Nuclear Magnetic Resonance (1H NMR) metabonomics to assess the metabolic profiles associated with five TCM syndrome types of WD-related liver fibrosis and analyzed the diagnostic and predictive capabilities of various metabolites. The study found a variety of metabolites, each with varying levels of diagnostic and predictive capabilities. Furthermore, the discerned differential metabolic pathways were primarily associated with various pathways involving carbohydrate metabolism, amino acid metabolism, and lipid metabolism. This study has identified various characteristic metabolic markers and pathways associated with different TCM syndromes of liver fibrosis in WD, providing a substantial foundation for investigating the mechanisms underlying these TCM syndromes.

Measures of explained variation under the mixture cure model for survival data

Explained variation is well understood under linear regression models and has been extended to models for survival data. In this article, we consider the mixture cure models. We propose two approaches to define explained variation under the mixture cure models, one based on the Kullback-Leibler information gain and the other based on residual sum of squares. We show that the proposed measures have desired properties as measures of explained variation, similar to those under other regression models. A simulation study is conducted to demonstrate the properties of the proposed measures. They are also applied to real data analyses to illustrate the use of explained variation.

The Impact of Graft CD3+ T-Cell Dose on the Outcome of T-Cell Replete Human Leukocyte Antigen-Mismatched Allogeneic Hematopoietic Peripheral Blood Stem Cells Transplantation

Background

Data on whether the graft CD3-positive (CD3⁺) T-cell dose in T-cell-replete human leukocyte antigen (HLA)-mismatched allogeneic hematopoietic peripheral blood stem cells transplantation (PBSCT) influences post-transplant outcomes are controversial.

Methods

Using King Hussein Cancer Center (KHCC) Blood and Marrow Transplantation (BMT) Registry database, 52 adult subjects, receiving the first T-cell-replete HLA-mismatched allogeneic hematopoietic PBSCT for acute leukemias or myelodysplastic syndrome, were identified, from January 2017 to December 2020. The cutoff value of graft CD3⁺ T-cell dose was identified using the receiver operating characteristic (ROC) formula and Youden's analysis. Subjects were divided into two cohorts: cohort 1 with low CD3⁺ T-cell dose (n = 34) and cohort 2 with high CD3⁺ T-cell dose (n = 18). Correlative analyses were performed between CD3⁺ T-cell dose and the risk of graft-versus-host disease (GvHD), relapse, relapse-free survival (RFS), and overall survival (OS). P-values were two-sided and considered significant when P < 0.05.

Results

Subject covariates were displayed. Subject's characteristics were comparable, except for higher nucleated cells and more female donors in the high CD3⁺ T-cell cohort. The 100-day cumulative incidence of acute GvHD (aGvHD) was 45±7% and 3-year cumulative incidence of chronic GvHD (cGvHD) was 28±6.7%. There was no statistically significant difference between the two cohorts in aGvHD (50% vs. 39%, P = 0.4) or cGvHD (29% vs. 22%, P = 0.7). The 2-year cumulative incidence of relapse (CIR) was 67.5±16.3% for low compared with 14.3±6.8% for high CD3⁺ T-cell cohort (P = 0.018). Fifteen subjects relapsed and 24 have died, 13 due to disease relapse. There was an improvement in 2-year RFS (94% vs. 83%; P = 0.0022) and 2-year OS (91% vs. 89%; P = 0.025) in low CD3⁺ T-cell cohort compared with high CD3⁺ T-cell cohort. Graft CD3⁺ T-cell dose is the only significant risk factor for relapse (P = 002), and OS (P = 0.030) in univariate analysis which was maintained in multivariate for relapse (P = 0.003), but not for OS (P = 0.050).

Conclusions

Our data suggest that high graft CD3⁺ T-cell dose is associated with lower risk of relapse, and might improve long-term survival, but has no influence on the risk of developing aGvHD or cGvHD.

The association between iron status and thyroid hormone levels during pregnancy

BACKGROUND

Iron deficiency may be a risk factor for thyroid disorder; however, the relationship between iron deficiency and thyroid disorder as well as mechanism involved remain unclear.

METHODS

A hospital-based cross-sectional study was conducted to analyze the correlation between iron status and thyroid hormone levels in pregnant women. A total of 2218 pregnant women were recruited, and iron status and thyroid hormones were measured. Canonical correlation, Lasso regression, and Receiver operator characteristic (ROC) curve analysis were used to determine the association and related factors.

RESULTS

There were 219 cases with iron deficiency anemia (IDA), 168 cases with iron deficiency (ID), and 1831 subjects with normal iron status. Compared with normal group, free triiodothyronine (FT3) and free thyroxine (FT4) in ID group and IDA group had a significant decreasing trend (P < 0.05), with the lowest levels in IDA group. Thyroid stimulating hormone (TSH) was significantly increased in ID group and IDA group (P < 0.05). Moreover, the proportion of hypothyroidism in both ID group and IDA group was higher than the normal group, meanwhile the proportion of hyperthyroidism was lower in both groups (P < 0.05). Serum ferritin (SF) and hemoglobin (Hb) were positively correlated with FT3 and FT4 but negatively correlated with TSH. Correlation analysis indicated that iron status was associated with thyroid hormone levels (P < 0.05). Lasso regression analysis showed that SF, Hb and other variables could be included in the prediction model of FT4. The variables selected by Lasso model were used for ROC curve analysis, and the prediction accuracy was acceptable (AUC=0.778, P < 0.05).

CONCLUSION

Our study indicated that there is an association between iron status and thyroid hormone levels in pregnant women, and the level of FT4 may change with iron status. Our findings provide new ideas for regulating the thyroid hormone levels to prevent thyroid dysfunction during pregnancy.

Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study

BACKGROUND

Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRC patients.

MATERIALS AND METHODS

A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran's three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve.

RESULTS

The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRC patients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650-0.734), as well as 0.627 (0.670, 0.686) in the test data.

CONCLUSION

We improved a novel nomogram diagram according to factors for predicting OS in CRC patients, which could assist clinical decision-making and prognosis predictions in patients with CRC.