A Nomogram Based on Circulating CD4+ T Lymphocytes and Lactate Dehydrogenase to Predict Distant Metastasis in Patients with Nasopharyngeal Carcinoma

Serum ferritin predicted prognosis in patients with nasopharyngeal carcinoma

Elevated serum ferritin (SF) levels have been associated with poor prognosis in various cancer types, but its impact on nasopharyngeal carcinoma (NPC) remains unclear. This retrospective study analyzed clinical data from 252 non-metastatic NPC patients admitted to Hainan General Hospital between January 2014 and May 2016. SF levels were measured using the chemiluminescence method. Patients were categorized into low, medium, and high-level SF groups based on tertile median SF levels. Survival outcomes were assessed using Kaplan-Meier analysis and Cox regression models. The overall survival rates of the entire patient cohort at 1, 3, 5, and 8 years were 95.2%, 85.7%, 76.2%, and 68.9% respectively. The high-level SF group (SF > 164.00 ng/mL) had significantly worse overall survival (83.1 vs 96.3 months, P = 0.023) and progression-free survival (77.8 vs 93.3 months, P = 0.019) compared to the low-level SF group. Univariate and multivariate analyses confirmed that high SF levels, along with T3/T4 staging and N3 staging, were independent risk factors for poor prognosis. In conclusion, high SF levels are associated with shorter overall survival and progression-free survival in NPC patients.

CD4 levels and NSCLC metastasis: the benefits of maintaining moderate levels

OBJECTIVES

Prior researches indicate that peripheral blood CD4 levels have an inverse correlation with distant tumor metastasis in non-small cell lung cancer (NSCLC). However, the linear relationship between CD4 and distant metastasis lacks clarity. Hence, the objective of this study was to ascertain the linear relationship between CD4 and distant metastasis in NSCLC patients.

METHODS

This retrospective study analyzed clinical and laboratory data of NSCLC patients between March 2016 and July 2022 at the Cancer Hospital of Anhui University of Technology. The study first applied a generalized summation model and smoothing curve fitting to determine if there was a linear relationship between CD4 and NSCLC metastasis. Secondarily, univariate logistic analysis and multiple linear regression were used to analyze the odds ratio (OR) of CD4 as a continuous variable, dichotomous variable, and trichotomous variable when predicting NSCLC metastasis. In addition, stratified and subgroup analyses were conducted to assess the reliability of CD4 in different NSCLC patient populations.

RESULTS

The study included a total of 213 NSCLC patients, among which 122 had distant metastasis and 91 had no metastasis. The smoothing curve fitting analysis revealed a U-shaped relationship between CD4 and NSCLC metastasis with a threshold effect. The univariate logistic analysis indicated that continuous CD4 expression was not significantly associated with NSCLC metastasis (P = 0.051); however, high levels of CD4 expression (≥ 35.06%) were found to be a protective factor against NSCLC metastasis when CD4+ T was a dichotomous variable (OR = 0.49, P = 0.010). Furthermore, multivariate linear regression models showed that low (< 32%) or high levels (> 44%) of CD4 significantly increased the risk of NSCLC metastasis compared to medium levels (32-44%) when CD4+ T was trichotomized. The significance was maintained in stratified analysis in relation to age, sex, type of pathology, smoke, PS, and T stage. CD4 levels were U-shaped in relation to different sites of distant metastases (bone, brain, liver), but not with lung metastases.

CONCLUSIONS

A threshold effect is shown to exist between the peripheral blood CD4 and distant metastasis in NSCLC patients. It was revealed that the risk of distant metastasis is lower when CD4 is maintained between 32 and 44%, whereas low (< 32%) or high (> 44) levels of CD4 are associated with an increased risk of distant metastasis in NSCLC patients.

Adjuvant chemotherapy or no adjuvant chemotherapy? A prediction model for the risk stratification of recurrence or metastasis of nasopharyngeal carcinoma combining MRI radiomics with clinical factors

BACKGROUND

Dose adjuvant chemotherapy (AC) should be offered in nasopharyngeal carcinoma (NPC) patients? Different guidelines provided the different recommendations.

METHODS

In this retrospective study, a total of 140 patients were enrolled and followed for 3 years, with 24 clinical features being collected. The imaging features on the enhanced-MRI sequence were extracted by using PyRadiomics platform. The pearson correlation coefficient and the random forest was used to filter the features associated with recurrence or metastasis. A clinical-radiomics model (CRM) was constructed by the Cox multivariable analysis in training cohort, and was validated in validation cohort. All patients were divided into high- and low-risk groups through the median Rad-score of the model. The Kaplan-Meier survival curves were used to compare the 3-year recurrence or metastasis free rate (RMFR) of patients with or without AC in high- and low-groups.

RESULTS

In total, 960 imaging features were extracted. A CRM was constructed from nine features (seven imaging features and two clinical factors). In the training cohort, the area under curve (AUC) of CRM for 3-year RMFR was 0.872 (P <0.001), and the sensitivity and specificity were 0.935 and 0.672, respectively; In the validation cohort, the AUC was 0.864 (P <0.001), and the sensitivity and specificity were 1.00 and 0.75, respectively. Kaplan-Meier curve showed that the 3-year RMFR and 3-year cancer specific survival (CSS) rate in the high-risk group were significantly lower than those in the low-risk group (P <0.001). In the high-risk group, patients who received AC had greater 3-year RMFR than those who did not receive AC (78.6% vs. 48.1%) (p = 0.03).

CONCLUSION

Considering increasing RMFR, a prediction model for NPC based on two clinical factors and seven imaging features suggested the AC needs to be added to patients in the high-risk group and not in the low-risk group.

Lung Immune Prognostic Index Could Predict Metastasis in Patients With Osteosarcoma

Background

The lung immune prognostic index (LIPI), composed of serum lactate dehydrogenase (LDH) and the derived neutrophil to lymphocyte ratio (dNLR), is a novel prognostic factor of lung cancer. The prognostic effect of the LIPI has never been verified in osteosarcoma.

Methods

We retrospectively reviewed the osteosarcoma patients with metachronous metastasis from January 2016 to January 2021 in West China Hospital. We collected and analyzed the clinical data and constructed the LIPI for osteosarcoma. The correlation between the LIPI and metastasis was analyzed according to the Kaplan–Meier method and Cox regression analysis with hazard ratios (HRs) and 95% confidence intervals (CIs). Univariate analysis and multivariate analysis were conducted to clarify the independent risk factors of metastasis. The nomogram model was established by R software, version 4.1.0.

Results

The area under the curve (AUC) and best cutoff value were 0.535 and 91, 0.519, and 5.02, 0.594 and 2.77, 0.569 and 227.14, 0.59 and 158, and 0.607 and 2.05 for ALP, LMR, NLR, PLR, LDH, and dNLR, respectively. The LIPI was composed of LDH and dNLR and showed a larger AUC than other hematological factors in the time-dependent operator curve (t-ROC). In total, 184 patients, 42 (22.8%), 96 (52.2%), and 46 (25.0%) patients had LIPIs of good, moderate, and poor, respectively (P &lt; 0.0001). Univariate analysis revealed that pathological fracture, the initial CT report of suspicious nodule, and the NLR, PLR, ALP, and the LIPI were significantly associated with metastasis, and multivariate analysis showed that the initial CT report of suspicious nodule and the PLR, ALP, and LIPI were dependent risk factors for metastasis. Metastatic predictive factors were selected and incorporated into the nomogram construction, including the LIPI, ALP, PLR, initial CT report, and pathological fracture. The C-index of our model was 0.71. According to the calibration plot, this predictive nomogram could accurately predict 3- and 5-year metachronous metastasis. Based on the result of decision curve and clinical impact curve, this predictive nomogram could also help patients obtain significant net benefits.

Conclusion

We first demonstrated the metastatic predictive effect of the LIPI on osteosarcoma. This LIPI-based model is useful for clinicians to predict metastasis in osteosarcoma patients and could help conduct timely intervention and facilitate personalized management of osteosarcoma patients.