The Coefficient of Variation of Red Blood Cell Distribution Width Combined with Cancer Antigen 125 Predicts Postoperative Overall Survival in Endometrial Cancer

Development and validation of a prognostic nomogram model incorporating routine laboratory biomarkers for preoperative patients with endometrial cancer

BACKGROUND

Some biomarkers collected from routine laboratory tests have shown important value in cancer prognosis. The study aimed to evaluate the prognostic significance of routine laboratory biomarkers in patients with endometrial cancer (EC) and to develop credible prognostic nomogram models for clinical application.

METHODS

A total of 727 patients were randomly divided into a training set and a validation set. Cox proportional hazards models were used to evaluate each biomarker's prognostic value, and independent prognostic factors were used to generate overall survival (OS) and progression-free survival (PFS) nomgrams. The efficacy of the nomograms were evaluated by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, X-tile analysis and Kaplan‒Meier curves.

RESULTS

Ten significant biomarkers in multivariate Cox analysis were integrated to develop OS and PFS nomograms. The C-indices of the OS- nomogram in the training and validation sets were 0.885 (95% confidence interval (CI), 0.810-0.960) and 0.850 (95% CI, 0.761-0.939), respectively; those of the PFS- nomogram in the training and validation sets were 0.903 (95% CI, 0.866-0.940) and 0.825 (95% CI, 0.711-0.939), respectively. ROC, DCA and calibration curves showed better clinical application value for the nomograms incorporating routine laboratory biomarkers. X-tile analysis and Kaplan‒Meier curves showed that the nomograms were stable and credible in evaluating patients at different risks.

CONCLUSIONS

Nomogram models incorporating routine laboratory biomarkers, including NLR, MLR, fibrinogen, albumin and AB blood type, were demonstrated to be simple, reliable and favourable in predicting the outcomes of patients with EC.

Clinical Relevance of Red Blood Cell Distribution Width (RDW) in Endometrial Cancer: A Retrospective Single-Center Experience from Korea

BACKGROUND

Red blood cell distribution width (RDW) is a standard parameter of complete blood count and indicates the variability in red blood cell size. This study aimed to determine whether preoperative RDW can be used to predict the recurrence and prognosis of endometrial carcinoma.

METHODS

The medical records of 431 patients diagnosed with endometrial carcinoma were retrospectively reviewed between May 2006 and June 2018. In addition to RDW, the clinicopathological factors, survival curves, and prognoses of the patients with endometrial carcinoma were compared between the high (n = 213) and low (n = 218) groups according to the median RDW value (12.8%).

RESULTS

The patients with high RDW had significantly advanced-stage (p = 0.00) pelvic lymph node metastasis (p = 0.01) and recurrence (p = 0.01) compared to those in the low-RDW group. In univariate analysis with DFS as the endpoint, surgical stage, type II histology, grade, RDW, and lymph node metastasis were independently associated with survival. Patients with high RDW values had significantly shorter disease-free survival and overall survival than those with low RDW values (log-rank p = 0.03, log-rank p = 0.04, respectively).

CONCLUSION

Our results demonstrate that RDW is a simple and convenient indicator of endometrial carcinoma recurrence. Prospective studies are needed to validate the findings of the current study.

A combined preoperative red cell distribution width and carcinoembryonic antigen score contribute to prognosis prediction in stage I lung adenocarcinoma

AIMS

Hematological markers that can be used for prognosis prediction for stage I lung adenocarcinoma (LUAD) are still lacking. Here, we examined the prognostic value of a combination of the red cell distribution width (RDW) and carcinoembryonic antigen (CEA), namely, the RDW-CEA score (RCS), in stage I LUAD.

MATERIALS AND METHODS

A retrospective study with 154 patients with stage I LUAD was conducted. Patients were divided into RCS 1 (decreased RDW and CEA), RCS 2 (decreased RDW and increased CEA, increased RDW and decreased CEA), and RCS 3 (increased RDW and CEA) subgroups based on the best optimal cutoff points of RDW and CEA for overall survival (OS). The differences in other clinicopathological parameters among RCS subgroups were calculated. Disease-free survival (DFS) and OS among these groups were determined by Kaplan-Meier analysis, and risk factors for outcome were calculated by a Cox proportional hazards model.

RESULTS

Seventy, 65, and 19 patients were assigned to the RCS 1, 2, and 3 subgroups, respectively. Patients ≥ 60 years (P < 0.001), male sex (P = 0.004), T₂ stage (P = 0.004), and IB stage (P = 0.006) were more significant in the RCS 2 or 3 subgroups. The RCS had a good area under the curve (AUC) for predicting DFS (AUC = 0.81, P < 0.001) and OS (AUC = 0.93, P < 0.001). The DFS (log-rank = 33.26, P < 0.001) and OS (log-rank = 42.05, P < 0.001) were significantly different among RCS subgroups, with RCS 3 patients displaying the worst survival compared to RCS 1 or 2 patients. RCS 3 was also an independent risk factor for both DFS and OS.

CONCLUSIONS

RCS is a useful prognostic indicator in stage I LUAD patients, and RCS 3 patients have poorer survival. However, randomized controlled trials are needed to validate our findings in the future.

Preoperative Prediction Value of Pelvic Lymph Node Metastasis of Endometrial Cancer: Combining of ADC Value and Radiomics Features of the Primary Lesion and Clinical Parameters

Objective

To investigate the value of apparent diffusion coefficient (ADC) value of endometrial cancer (EC) primary lesion and magnetic resonance imaging (MRI) three-dimensional (3D) radiomics features combined with clinical parameters for preoperative prediction of pelvic lymph node metastasis (PLNM).

Methods

A total of 136 patients with EC confirmed by postoperative pathology were retrospectively reviewed and analyzed. Patients were randomly divided into training set (n = 95) and test set (n = 41) at a ratio of 7 : 3. Radiomics features based on T₂WI, DWI, and contrast-enhanced T₁WI (CE-T₁WI) sequence were extracted and screened, and then radiomics score (Rads-score) was calculated. Clinical parameters and ADC value of EC primary lesion were measured and collected, and their correlation with PLNM was analyzed. Receiver operating characteristic (ROC) curve was plotted to assess the diagnostic efficacy of the model. A nomogram for PLNM was created based on the multivariate logistic regression model.

Results

The ADC value of the EC primary lesion showed inverse correlation with PLNM, while CA125 and Rads-score were positively associated with PLNM. A predictive model was proposed based on ADC value, Rads-score, CA125, and MR-reported pelvic lymph node status (PLNS) for PLNM in EC. The area under the curve (AUC) of the model is 0.940; the sensitivity and specificity (87.1% and 90.6%) of the model were significantly higher than that of the MRI morphological signs.

Conclusion

A combination of ADC value, MRI 3D radiomics features of the EC primary lesion, and clinical parameters generated a prediction model for PLNM in EC and had a good diagnostic performance; it was a useful supplement to MR-reported PLNS based on MRI morphological signs.