Nomograms based on the novel platelet index score predict postoperative prognosis in endometrial cancer

The inflammatory markers combined with CA125 may predict postoperative survival in endometrial cancer

BACKGROUND

Endometrial cancer (EC) has a high latency, making prognosis difficult to predict. Cancer antigen 125 (CA125) is not specific as a tumour marker for EC; however, complete blood count (CBC) inflammatory markers are associated with prognosis in various malignancies. Thus, this study investigated the value of CBC inflammatory markers combined with CA125 levels in predicting the prognosis of patients with EC.

METHODS

In this study, 517 patients with EC were recruited between January 2015 and January 2022, and clinical characteristics, CBC inflammatory markers, and CA125 levels were assessed. Differences in each index at different EC stages and the correlation between the index and EC stage were analysed, and the influence of the index on EC prognosis was evaluated.

RESULTS

Platelet distribution width (PDW) levels were significantly lower in patients with advanced EC than in those with early EC, whereas the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and CA125 levels were significantly higher in patients with advanced EC (all P < 0.05). ROC curve and multivariate logistic regression analyses indicated that decreased PDW and increased CA125 levels were independent risk factors for EC staging progression. In addition, multivariate Cox regression analysis showed that the combination of low PDW and high CA125 (PDW + CA125 = 2) was an independent prognostic factor of survival in EC patients. Kaplan-Meier survival analysis indicated that patients with low PDW and high CA125 had worse overall survival.

CONCLUSIONS

The PDW and CA125 score may be an independent prognostic factor for postoperative overall survival in patients with EC and a useful marker for predicting the prognosis of these patients.

Advancing Tailored Treatments: A Predictive Nomogram, Based on Ultrasound and Laboratory Data, for Assessing Nodal Involvement in Endometrial Cancer Patients

Assessing lymph node metastasis is crucial in determining the optimal therapeutic approach for endometrial cancer (EC). Considering the impact of lymphadenectomy, there is an urgent need for a cost-effective and easily applicable method to evaluate the risk of lymph node metastasis in cases of sentinel lymph node (SLN) biopsy failure. This retrospective monocentric study enrolled EC patients, who underwent surgical staging with nodal assessment. Data concerning demographic, clinicopathological, ultrasound, and surgical characteristics were collected from medical records. Ultrasound examinations were conducted in accordance with the IETA statement. We identified 425 patients, and, after applying exclusion criteria, the analysis included 313 women. Parameters incorporated into the nomogram were selected via univariate and multivariable analyses, including platelet count, myometrial infiltration, minimal tumor-free margin, and CA 125. The nomogram exhibited good accuracy in predicting lymph node involvement, with an AUC of 0.88. Using a cutoff of 10% likelihood of nodal involvement, the nomogram displayed a low false-negative rate of 0.04 (95% CI 0.00-0.19) in the training set. The adaptability of this straightforward model renders it suitable for implementation across diverse clinical settings, aiding gynecological oncologists in preoperative patient evaluations and facilitating the design of personalized treatments. However, external validation is mandatory for confirming diagnostic accuracy.

A prognostic nomogram that includes MPV in esophageal squamous cell carcinoma

BACKGROUND

Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients.

METHODS

The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO-cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity.

RESULTS

Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1-, 3-, and 5-year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts.

CONCLUSIONS

The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients.

A novel predictive model based on inflammatory response-related genes for predicting endometrial cancer prognosis and its experimental validation

Inflammatory response is an important feature of most tumors. Local inflammation promotes tumor cell immune evasion and chemotherapeutic drug resistance. We aimed to build a prognostic model for endometrial cancer patients based on inflammatory response-related genes (IRGs). RNA sequencing and clinical data for uterine corpus endometrial cancer were obtained from TCGA datasets. LASSO-penalized Cox regression was used to obtain the risk formula of the model: the score = e^{sum(corresponding coefficient × each gene's expression)}. The "ESTIMATE" and "pRRophetic" packages in R were used to evaluate the tumor microenvironment and the sensitivity of patients to chemotherapy drugs. Data sets from IMvigor210 were used to evaluate the efficacy of immunotherapy in cancer patients. For experimental verification, 37 endometrial cancer and 43 normal endometrial tissues samples were collected. The mRNA expression of the IRGs was measured using qRT-PCR. The effects of IRGs on the malignant biological behaviors of endometrial cancer were detected using CCK-8, colony formation, Transwell invasion, and apoptosis assays. We developed a novel prognostic signature comprising 13 IRGs, which is an independent prognostic marker for endometrial cancer. A nomogram was developed to predict patient survival accurately. Three key IRGs (LAMP3, MEP1A, and ROS1) were identified in this model. Furthermore, we verified the expression of the three key IRGs using qRT-PCR. Functional experiments also confirmed the influence of the three key IRGs on the malignant biological behavior of endometrial cancer. Thus, a characteristic model constructed using IRGs can predict the survival, chemotherapeutic drug sensitivity, and immunotherapy response in patients with endometrial cancer.

Relation of Mean Platelet Volume (MPV) with Cancer: A Systematic Review with a Focus on Disease Outcome on Twelve Types of Cancer

Inflammatory proteins activate platelets, which have been observed to be directly related to cancer progression and development. The aim of this systematic review is to investigate the possible association between Mean Platelet Volume (MPV) and cancer (diagnostic capacity of MPV, relation to survival, the severity of the disease, and metastasis). A literature review was performed in the online database PubMed and Google Scholar for the period of 2010–2022. In total, 83 studies including 21,034 participants with 12 different types of cancer (i.e., gastric cancer, colon cancer, esophageal squamous cell carcinoma, renal cancer, breast cancer, ovarian cancer, endometrial cancer, thyroid cancer, lung cancer, bladder cancer, gallbladder cancer, and multiple myeloma) were identified. The role of MPV has been extensively investigated in several types of cancer, such as gastric, colon, breast, and lung cancer, while few data exist for other types, such as renal, gallbladder cancer, and multiple myeloma. Most studies in gastric, breast, endometrium, thyroid, and lung cancer documented an elevated MPV in cancer patients. Data were less clear-cut for esophageal, ovarian, and colon cancer, while reduced MPV was observed in renal cell carcinoma and gallbladder cancer. Several studies on colon cancer (4 out of 6) and fewer on lung cancer (4 out of 10) indicated an unfavorable role of increased MPV regarding mortality. As far as other cancer types are concerned, fewer studies were conducted. MPV can be used as a potential biomarker in cancer diagnosis and could be a useful tool for the optimization of treatment strategies. Possible underlying mechanisms between cancer and MPV are discussed. However, further studies are needed to elucidate the exact role of MPV in cancer progression and metastasis.

Nomograms Based on Fibrinogen, Albumin, Neutrophil-Lymphocyte Ratio, and Carbohydrate Antigen 125 for Predicting Endometrial Cancer Prognosis

Background: This study aimed to determine the prognostic value of the preoperative levels of fibrinogen, albumin (ALB), neutrophil−lymphocyte ratio (NLR), and carbohydrate antigen 125 (CA125) in endometrial cancer and to establish nomograms for predicting patient survival. Methods: Patients with endometrial cancer (n = 1483) who underwent surgery were included in this study, and their preoperative fibrinogen, ALB, NLR, and CA125 levels and clinicopathological characteristics were collected. Patients were randomized into a training cohort (70%, n = 1038) and an external validation cohort (30%, n = 445). The Cox regression analysis was performed using the data for the patients in the training cohort to identify independent prognostic factors; nomograms for predicting prognosis were established and validated. Results: High fibrinogen (≥3.185 g/L), NLR (≥2.521 g/L), and CA125 (≥35 U/mL) levels and low ALB (<4.185 g/L) levels were independently associated with poor progression-free survival (PFS) and poor overall survival (OS) in patients with endometrial cancer. Prognostic prediction model nomograms were developed and validated based on these results. Calibration curves and C-indexes underscored the good predictive power of the nomograms, and both the net reclassification index (NRI) and integrated discrimination improvement (IDI) values of the prognostic prediction model nomograms were improved. Conclusions: Nomograms that are developed based on preoperative fibrinogen, ALB, NLR, and CA125 levels accurately predict PFS and OS in patients with endometrial cancer.

Preoperative Platelet Distribution Width Represents a Novel Prognostic Biomarker in Patients With Nonmetastatic Renal Cell Carcinoma: A Retrospective Clinical Analysis

Purpose

The study aimed to explore the prognostic value of platelet distribution width (PDW) in patients with nonmetastatic renal cell carcinoma (RCC).

Methods

We retrospective analyzed 706 patents with nonmetastatic RCC from January 2015 to December 2017. Clinicopathologic data and platelet indices were collected and analyzed by univariable and multivariable cox proportional hazard model. Progression-free survival (PFS) was analyzed using the Kaplan–Meier curve. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were performed to evaluate the improvement of predictive accuracy.

Results

Patients were divided into low PDW (N = 241, PDW ≤11.7%), intermediate PDW (N = 232, 11.7%< PDW ≤15.6%), and high PDW (N = 233, PDW >15.6%) groups according to the tertiles. Patients with low PDW were associated with more symptoms at presentation, larger tumor size, higher AJCC tumor stage, and more sarcomatoid differentiation. Besides, patients with low PDW had significantly shorter PFS compared to intermediate PDW and high PDW groups. On the multivariable model, AJCC tumor stage, nuclear grade, and PDW (either continuous or categorical variables) were independent factors correlated with PFS. The NRI and IDI showed adding PDW to SSIGN score improves its predictive accuracy related to 2-, 3-, and 4-year PFS.

Conclusions

Low PDW was related to advanced clinicopathologic features and worse prognosis in patients with nonmetastatic RCC. Thus, PDW could serve as a novel biomarker for risk stratification in these patients when used pre-or postoperatively.

Sera Protein Signatures of Endometrial Cancer Lymph Node Metastases

The presence of lymph node metastases in endometrial cancer patients is a critical factor guiding treatment decisions; however, surgical and imaging methods for their detection are limited by morbidity and inaccuracy. To determine if sera can predict the presence of positive lymph nodes, sera collected from endometrial cancer patients with or without lymph node metastases, and benign gynecology surgical patients (N = 20 per group) were subjected to electron spray ionization mass spectrometry (ES-MS). Peaks that were significantly different among the groups were evaluated by leave one out cross validation (LOOCV) for their ability to differentiation between the groups. Proteins in the peaks were identified by MS/MS of five specimens in each group. Ingenuity Pathway Analysis was used to predict pathways regulated by the protein profiles. LOOCV of sera protein discriminated between each of the group comparisons and predicted positive lymph nodes. Pathways implicated in metastases included loss of PTEN activation and PI3K, AKT and PKA activation, leading to calcium signaling, oxidative phosphorylation and estrogen receptor-induced transcription, leading to platelet activation, epithelial-to-mesenchymal transition and senescence. Upstream activators implicated in these events included neurostimulation and inflammation, activation of G-Protein-Coupled Receptor Gβγ, loss of HER-2 activation and upregulation of the insulin receptor.

Systemic Immune-Inflammatory Index as a Predictor of Lymph Node Metastasis in Endometrial Cancer

Purpose

This study assessed the predictive value of the preoperative systemic immune-inflammatory index (SII) for lymph node metastasis (LNM) in endometrial cancer (EC) patients.

Methods

We retrospectively included 392 EC patients between January 2013 and January 2019. Data on clinical indicators including age, body mass index (BMI), menopause, serum inflammatory immune index, serum tumor markers, history of diabetes and hypertension, stage, histological type, and myometrial invasion (MI) were collected. The association between clinical indicators and LNM was evaluated.

Results

The results indicated that neutrophil (NE), monocyte (MO) counts, SII, cancer antigen 125 (CA125), cancer antigen 153 (CA153), cancer antigen 199 (CA199), and the expression of estrogen receptor (ER) and Ki67 were higher in EC patients with LNM than in those without LNM (P<0.05). Lymph vascular space invasion (LVSI) was also associated with LNM (P<0.05). Consequently, the SII, CA125, CA153 and LVSI were found to be independent risk factors for LNM, and a nomogram including these indicators was performed. The ROC curve analysis showed that compared with a single index, the combination of the SII, CA125, CA153 and LVSI significantly improved the efficiency of diagnosing LNM in EC patients (AUC=0.865, P < 0.001). Moreover, the SII was significantly associated with age, menopause, and FIGO stage (P < 0.05). Further logistic regression analysis suggested that elevated serum SII was an independent risk factor for MI and progression to a higher pathological grade in young premenopausal EC patients. In addition, elevated SII was an independent risk factor for advanced EC progression in age ≥55 or postmenopausal EC patients.

Conclusion

An elevated SII is an independent risk factor for LNM in patients with EC. In addition, the SII can be used as a predictor of MI and higher pathological grade in young premenopausal EC patients.

Development and validation of nomogram based on a novel platelet index score to predict prognosis in patients with renal cell carcinoma

Purpose: This study aims to develop and validate a nomogram based on a novel platelet index score (PIS) to predict prognosis in patients with renal cell carcinoma (RCC).

Patients and methods: We retrospectively analyzed the data of 759 consecutive patients with RCC. The Kaplan-Meier curves were performed to analyze the platelet parameters and PIS was established. The patients were randomly divided into training (N=456, 60%) and validation cohorts (N=303, 40%). The nomogram was created based on the factors determined by multivariable Cox proportional hazard regression of the training cohort. We assessed the discrimination and calibration of our nomogram in both training and validation cohorts. And then the nomogram was compared with other reported models.

Results: High platelet count (PLT>285×10⁹/L) and low platelet distribution width (PDW≤10.95fL) were associated with shorter progression-free survival (PFS). Thus, PLT and PDW were incorporated in a novel score system called PIS. On multivariable analysis of training cohort, PIS, American Joint Committee on Cancer (AJCC) stage, and sarcomatoid differentiation were independent prognostic factors, which were all selected into the nomogram. The nomogram exhibited good discrimination in both training (C-index: 0.835) and validation cohorts (C-index: 0.883). The calibration curves also showed good agreement between prediction and observation in both cohorts. The C-index of the nomogram (C-index: 0.810~0.902) for predicting 2-year, 3-year, and 4-year PFS were significantly higher than Leibovich (C-index: 0.772~0.813), SSIGN (C-index: 0.775~0.876), Cindolo (C-index: 0.642~0.798), Yaycioglu (C-index: 0.648~0.804), MSKCC (C-index: 0.761~0.862), Karakiewicz (C-index: 0.747~0.851), and AJCC stage models (C-index: 0.759~0.864).

Conclusion: The nomogram based on a novel PIS could offer better risk stratification in patients with RCC.

The pretreatment platelet count predicts survival outcomes of diffuse large B-cell lymphoma: An analysis of 1007 patients in the rituximab era

BACKGROUND

The prognostic value of platelet count in diffuse large B-cell lymphoma (DLBCL) has not been extensively investigated. We aimed to examine the association of pretreatment platelet count with disease features, and further examine the prognostic significance of platelet count in DLBCL treated with the R-CHOP regimen.

METHODS

Patients with DLBCL diagnosed between Jan 1 st, 2005 and Dec 31 st, 2018 at Cancer Hospital, Chinese Academy of Medical Sciences were retrospectively analyzed. Propensity score matching (PSM) was used to balance confounding factors.

RESULTS

A total of 1007 eligible patients who received frontline R-CHOP or R-CHOP-like regimens were included in this study. The optimal cutoff value of platelet count was 157 × 10⁹/L, as determined by the Maximally Selected Rank Statistics method. Patients with the platelet count ≤157 × 10⁹/L had significantly inferior overall survival (OS) (5-year OS, 44.4 % vs. 74.9 %, P < 0.001) and progression-free survival (PFS) (5-year PFS, 35.5 % vs. 65.9 %, P < 0.001) than those with the platelet count >157×10⁹/L. Multivariate analyses showed that pretreatment platelet count ≤ 157 × 10⁹/L was an adversely independent prognostic factor for OS (hazard ratio [HR] 1.960, 95 % confidence interval [CI] 1.418-2.709, P<0.001) and PFS (HR 1.443, 95 %CI 1.080-1.927, P = 0.013). The PSM analysis and subgroup analyses further confirmed the significantly negative impact of low platelet count on OS and PFS.

CONCLUSION

The pretreatment platelet count may be a simple, cost-effective and useful prognostic factor in DLBCL patients treated with frontline R-CHOP regimens. Further investigation is warranted to elucidate the biologic mechanism underlying the prognostic significance of platelet count in DLBCL.

[Prognostic value of preoperative platelet parameters in locally advanced renal cell carcinoma]

OBJECTIVE

To explore the prognostic value of preoperative platelet parameters in locally advanced renal cell carcinoma for the risk stratification of such patients.

METHODS

Clinical data of patients with locally advanced renal cell carcinoma in the Third Hospital of Peking University from January 2015 to December 2017 were collected. The patients were divided into progression group and progression-free group according to follow-up data, and preoperative platelet parameters and clinical data between the two groups were compared. The optimal cut-off value of platelet parameters was determined by receiver operating characteristic curve (ROC) and analyzed by Kaplan-Meier survival curve. Cox proportional hazards model was used to analyze the independent risk factors of PFS. Time dependent ROC curve, net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to evaluate the improvement of SSIGN model by incorporating platelet parameters.

RESULTS

Of the 215 patients, 192 (89.3%) were followed up for a median of 36 months. Sixty-four patients (29.8%) had disease progression during the follow-up, and the median PFS was 46 months. In progression group, the platelet count (PLT) was higher [(250.72 ± 88.59)×10⁹/L vs. (227.27 ± 66.94)×10⁹/L, P=0.042] and the platelet distribution width (PDW) was lower [(12.01 ± 2.27)% vs. (13.31 ± 2.74)%, P = 0.001] than that of progression-free groups. 285×10⁹ /L and 12.65% as the best cut-off values of PLT and PDW, the median PFS of PLT≤285×10⁹ /L group was significantly longer than that of PLT>285×10⁹ /L group (53 months vs. 41 months, P=0.033), and the median PFS of PDW>12.65% group was also significantly longer than that of PDW≤12.65% group (56 months vs. 41 months, P < 0.001). Multivariate analysis showed that preoperative PDW (HR=0.735, P < 0.001), nuclear grade Ⅲ to Ⅳ (HR=2.425, P=0.001) and sarcomatoid differentiation (HR=3.101, P=0.008) were independent risk factors for PFS. The area under the curve of PDW combined with SSIGN model was larger than that with the original SSIGN model [0.748 (95%CI: 0.662－0.833) vs. 0.678 (95%CI: 0.583－0.773), P=0.193], NRI was 0.262 (P=0.04), and IDI was 0.085 (P=0.01), indicating that the predictive ability of PDW combined with SSIGN model was improved.

CONCLUSION

Preoperative high PLT and low PDW are associated with adverse prognosis of locally advanced renal cell carcinoma, and PDW is an independent risk factor. Therefore, preoperative PDW could serve as biomarker for risk stratification of locally advanced renal cell carcinoma.

Low platelet/platelet distribution width and high platelet/lymphocyte ratio are adverse prognostic factors in patients with newly diagnosed advanced Hodgkin lymphoma

We conducted a retrospective study in 274 previously untreated advanced Hodgkin lymphoma (HL) patients to investigate the prognostic value of baseline platelet (PLT) count, platelet distribution width (PDW), mean platelet volume (MPV), and platelet/lymphocyte ratio (PLR). The median follow-up time was 89 (range 0.3-240) months. By univariate analysis, PLT/PDW <24.5, PLR ≥245, and MPV <8fl were all associated with worse freedom from progression (FFP), progression-free survival (PFS), and overall survival (OS). By multivariate analysis, PLT/PDW <24.5 was a risk factor for FFP (HR 2.02, p = 0.002) and PFS (HR 2.36, p < 0.001). PLR ≥245 was independently associated with inferior FFP (HR 2.04, p = 0.003) and PFS (HR 1.93, p = 0.002). Due to the limited number of death events, multivariate analysis was not conducted for OS. Propensity score matching analysis and subgroup analysis further validated the prognostic value for PLT/PDW and PLR. In conclusion, PLT/PDW and PLR are promising prognostic indicators for newly diagnosed advanced HL.