Combining Lactate Dehydrogenase and Fibrinogen: Potential Factors to Predict Therapeutic Efficacy and Prognosis of Patients with Small-Cell Lung Cancer

Diagnostic and Predictive Recurrence Value of Plasma Fibrinogen in Patients With Adrenocortical Carcinoma

Background

The correlation between fibrinogen levels and adrenocortical carcinoma (ACC) remains unclear. This study aimed to explore the value of preoperative plasma fibrinogen as a biomarker for ACC.

Methods

We identified 40 patients with ACC and 170 patients with adrenal adenoma (AA) who underwent surgery at our institution between 2015 and 2022. Plasma fibrinogen levels and postoperative tumor recurrence information of the patients were also recorded. For intergroup comparisons, data obtained from the AA and ACC groups were evaluated using a t-test. The cutoff value of fibrinogen level was determined using a receiver operating characteristic (ROC) curve.

Results

Mean fibrinogen levels in the AA and ACC groups were 2.81 ± 0.59 g/L and 3.88 ± 1.75 g/L, respectively (P < .001). Fibrinogen level, which can help distinguish between AA and ACC, was evaluated using the ROC curve. The cutoff fibrinogen level was estimated as 3.87 g/L according to the Youden index. With this value, the sensitivity was 62.5%, specificity was 95.7%, and the area under the ROC curve (AUC) was 0.74 (P < .001). Fibrinogen level, which can help distinguish between recurrence and non-recurrence, was evaluated using the ROC curve. The cutoff fibrinogen level was estimated as 3.96 g/L according to the Youden index. The sensitivity, specificity, and AUC were 90%, 71.4%, and 0.85, respectively (P < .001).

Conclusion

According to the data in this study, plasma fibrinogen could be used to distinguish ACC from AA. Most importantly, plasma fibrinogen may be used to identify recurrence of postoperative ACC.

Prognostic value of baseline clinicopathological characteristics in first-line chemotherapy ± immunotherapy for extensive-stage small cell lung cancer: a retrospective cohort study

Background

The integration of chemotherapy and immunotherapy as a first-line treatment for extensive-stage small cell lung cancer (ES-SCLC) has been adopted in clinical practice, yet the response to immune checkpoint inhibitors (ICIs) is variable, benefiting only a fraction of patients. The current absence of reliable biomarkers for predicting treatment response and prognosis represents a significant gap in knowledge, hindering the optimization of patient stratification and treatment planning. This retrospective cohort study aims to assess the potential predictive and prognostic significance of clinicopathological baseline features in ES-SCLC patients.

Methods

Our study retrospectively analyzed the data of consecutive patients with ES-SCLC treated with first-line etoposide plus platinum chemotherapy ± immunotherapy at The Affiliated Lihuili Hospital of Ningbo University from April 2017 to April 2023. Data on clinical information, serum laboratory indicators, pathological immunohistochemical markers, and progression-free survival (PFS) times were collected. Univariate and multivariate Cox regression analyses were employed to determine whether these indicators could serve as independent prognostic factors for PFS. Further, potential predictive markers for treatment efficacy were identified using a Cox regression model that incorporated an interaction term between treatment modality and the indicator.

Results

A total of 121 patients with ES-SCLC were enrolled in the study, of whom 62 received chemotherapy alone, and 59 received chemotherapy in combination with immunotherapy. Compared to chemotherapy alone, the addition of immunotherapy to first-line chemotherapy significantly extended the PFS time [P<0.001; hazard ratio (HR) =0.42; 95% confidence interval (CI): 0.28, 0.64] of the ES-SCLC patients. The multivariate analysis revealed that an immunochemotherapy regimen (P<0.001, HR =0.40; 95% CI: 0.24, 0.68), a low-density lipoprotein (LDL) level of >1.8 mmol/L (P=0.02; HR =0.41; 95% CI: 0.20, 0.85) were independent prognostic factors of favorable PFS in the first-line treatment of all ES-SCLC, while a lactate dehydrogenase (LDH) level of >273 U/L (P=0.04; HR =1.78; 95% CI: 1.03, 3.07), a neuron-specific enolase (NSE) concentration of >102.6 ng/mL (P=0.009; HR =6.49; 95% CI: 1.60, 26.32), an apolipoprotein A1 (ApoA1) concentration of >0.9 g/L (P<0.001; HR =4.15; 95% CI: 1.98, 8.71), and an apolipoprotein B (ApoB) concentration of >0.8 g/L (P=0.002; HR =2.24; 95% CI: 1.34, 3.75) were independent prognostic factors of poorer PFS. Further, the interaction effect analysis demonstrated that an LDL level of >1.8 mmol/L and the absence of bone metastasis were potential predictors of an improved response to ICI therapy compared to chemotherapy alone.

Conclusions

This study showed the survival benefit of receiving a chemoimmunotherapy regimen as the first-line treatment in a real-world scenario. It also suggests the prognostic significance of pre-treatment LDL, LDH, NSE, ApoA1, and ApoB with optimal cut-off values in the first-line treatment of all ES-SCLC, and the potential utility of baseline LDL level or the presence of bone metastasis in guiding first-line treatment strategies.

Preliminary investigation of elevated collagen and blood-clotting markers as potential noninvasive biomarkers for small cell lung cancer

BACKGROUND

Small cell lung cancer (SCLC) is highly aggressive with limited therapeutic options and a poor prognosis. Moreover, noninvasive biomarker tools for detecting disease and monitoring treatment response are lacking. To address this, we evaluated serum biomarkers of extracellular matrix proteins not previously explored in SCLC.

METHODS

We measured biomarkers in the serum of 16 patients with SCLC before and after chemotherapy as well as in the serum of 11 healthy individuals.

RESULTS

Our findings demonstrated that SCLC serum had higher levels of collagen type I degradation, collagen type III formation, and collagen type XI formation than healthy controls. In addition, we observed higher levels of type XIX and XXII collagens, fibrinogen, and von Willebrand factor A formation in SCLC serum. The formation of type I collagen did not exhibit any discernible variation. However, we observed a decrease in the degradation of type I collagen following chemotherapy.

CONCLUSION

Overall, our findings revealed elevated levels of collagen and blood-clotting markers in the serum of SCLC patients, indicating the potential of ECM proteins as noninvasive biomarkers for SCLC.

Prognostic Value of a Novel Parameter in Patients with Infective Endocarditis

Background

Infective endocarditis (IE) has a high rate of mortality and the prognosis of IE was poor. The purpose of this investigation was to explore the value of lactate dehydrogenase (LDH)/lymphocyte and compare it with LDH/lymphocyte percentage (L-LWR) in predicting the in-hospital mortality in IE patients.

Methods

The investigation cohort contained 147 IE patients between January 2017 and December 2019. We retrospectively went over the medical records and selected admission indexes.

Results

Compared with IE patients with adverse events, significantly higher levels of LDH/lymphocyte and significantly lower levels of L-LWR were discovered in IE patients without adverse events. After adjustments, L-LWR (odds ratio (OR): 4.558, 95% confidence interval (CI) 1.362-15.256, P = 0.014) still maintained its significant independence. In addition, L-LWR had the highest area under curve (AUC) (0.780, 0.704-0.844, P < 0.001) with good sensitivity (81.89%) and specificity (65.00%) when 34 was selected as the best cutoff value.

Conclusions

L-LWR is a reliable, low-priced, easily applicable, and independent prognostic parameter for in-hospital death with good performance in patients with IE.

Preoperative Breast Immune Prognostic Index as Prognostic Factor Predicts the Clinical Outcomes of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Objective

This study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT).

Methods

The optimal cutoff value was calculated through the receiver operating characteristic curve (ROC). The correlations between BIPI and clinicopathologic characteristics were determined by the chi-square test or Fisher’s exact test. The Kaplan–Meier method was used to estimate the survival probability, and the log-rank test was used to analyze the differences in the survival probability among patients. The univariate and multivariate Cox proportional hazard regression model was used to screen the independent prognostic factors. A prognostic nomogram for disease-free survival (DFS) and overall survival (OS) was built on the basis of the multivariate analyses. Furthermore, the calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram.

Results

All enrolled patients were split into three subgroups based on the BIPI score. The mean DFS and OS of the BIPI score 0 group and BIPI score 1 group were significantly longer than those of the BIPI score 2 group (42.02 vs. 38.61 vs. 26.01 months, 77.61 vs. 71.83 vs. 53.15 months; p < 0.05). Univariate and multivariate analyses indicated that BIPI was an independent prognostic factor for patients’ DFS and OS (DFS, hazard ratio (HR): 6.720, 95% confidence interval (CI): 1.629–27.717; OS, HR: 8.006, 95% CI: 1.638–39.119). A nomogram with a C-index of 0.873 (95% CI: 0.779–0.966) and 0.801 (95% CI: 0.702–0.901) had a favorable performance for predicting DFS and OS survival rates for clinical use by combining immune scores with other clinical features. The calibration curves at 1-, 3-, and 5-year survival suggested a good consistency between the predicted and actual DFS and OS probability. The DCA demonstrated that the constructed nomogram had better clinical predictive usefulness than only BIPI in predictive clinical applications of 5-year DFS and OS prognostic assessments.

Conclusions

The patients with low BIPI score have better prognoses and longer DFS and OS. Furthermore, the BIPI-based nomogram may serve as a convenient prognostic tool for breast cancer and help in clinical decision-making.