Diagnostic value of derived neutrophil-to-lymphocyte ratio in patients with ovarian cancer

Development and validation of an ultrasound-based deep learning radiomics nomogram for predicting the malignant risk of ovarian tumours

BACKGROUND

The timely identification and management of ovarian cancer are critical determinants of patient prognosis. In this study, we developed and validated a deep learning radiomics nomogram (DLR_Nomogram) based on ultrasound (US) imaging to accurately predict the malignant risk of ovarian tumours and compared the diagnostic performance of the DLR_Nomogram to that of the ovarian-adnexal reporting and data system (O-RADS).

METHODS

This study encompasses two research tasks. Patients were randomly divided into training and testing sets in an 8:2 ratio for both tasks. In task 1, we assessed the malignancy risk of 849 patients with ovarian tumours. In task 2, we evaluated the malignancy risk of 391 patients with O-RADS 4 and O-RADS 5 ovarian neoplasms. Three models were developed and validated to predict the risk of malignancy in ovarian tumours. The predicted outcomes of the models for each sample were merged to form a new feature set that was utilised as an input for the logistic regression (LR) model for constructing a combined model, visualised as the DLR_Nomogram. Then, the diagnostic performance of these models was evaluated by the receiver operating characteristic curve (ROC).

RESULTS

The DLR_Nomogram demonstrated superior predictive performance in predicting the malignant risk of ovarian tumours, as evidenced by area under the ROC curve (AUC) values of 0.985 and 0.928 for the training and testing sets of task 1, respectively. The AUC value of its testing set was lower than that of the O-RADS; however, the difference was not statistically significant. The DLR_Nomogram exhibited the highest AUC values of 0.955 and 0.869 in the training and testing sets of task 2, respectively. The DLR_Nomogram showed satisfactory fitting performance for both tasks in Hosmer-Lemeshow testing. Decision curve analysis demonstrated that the DLR_Nomogram yielded greater net clinical benefits for predicting malignant ovarian tumours within a specific range of threshold values.

CONCLUSIONS

The US-based DLR_Nomogram has shown the capability to accurately predict the malignant risk of ovarian tumours, exhibiting a predictive efficacy comparable to that of O-RADS.

Modeling mortality risk in patients with severe COVID-19 from Mexico

Background

Severe acute respiratory syndrome caused by a coronavirus (SARS-CoV-2) is responsible for the COVID-19 disease pandemic that began in Wuhan, China, in December 2019. Since then, nearly seven million deaths have occurred worldwide due to COVID-19. Mexicans are especially vulnerable to the COVID-19 pandemic as Mexico has nearly the worst observed case-fatality ratio (4.5%). As Mexican Latinos represent a vulnerable population, this study aimed to determine significant predictors of mortality in Mexicans with COVID-19 who were admitted to a large acute care hospital.

Methods

In this observational, cross-sectional study, 247 adult patients participated. These patients were consecutively admitted to a third-level referral center in Yucatan, Mexico, from March 1st, 2020, to August 31st, 2020, with COVID-19-related symptoms. Lasso logistic and binary logistic regression were used to identify clinical predictors of death.

Results

After a hospital stay of about eight days, 146 (60%) patients were discharged; however, 40% died by the twelfth day (on average) after hospital admission. Out of 22 possible predictors, five crucial predictors of death were found, ranked by the most to least important: (1) needing to be placed on a mechanical ventilator, (2) reduced platelet concentration at admission, (3) increased derived neutrophil to lymphocyte ratio, (4) increased age, and (5) reduced pulse oximetry saturation at admission. The model revealed that these five variables shared ~83% variance in outcome.

Conclusion

Of the 247 Mexican Latinos patients admitted with COVID-19, 40% died 12  days after admission. The patients' need for mechanical ventilation (due to severe illness) was the most important predictor of mortality, as it increased the odds of death by nearly 200-fold.

Predictive Value of Inflammatory and Nutritional Indexes in the Pathology of Bladder Cancer Patients Treated with Radical Cystectomy

In recent years, the focus of numerous studies has been the predictive value of inflammatory and nutritional parameters in oncology patients. The aim of our study was to examine the relationship between the inflammatory and nutritional parameters and the histopathological characteristics of patients with bladder cancer. A retrospective study included 491 patients who underwent radical cystectomy for bladder cancer between 2017 and 2021. We calculated the preoperative values of the neutrophil-to-lymphocyte ratio (NLR), the derived neutrophil-to-lymphocyte ratio (dNLR), the systemic immune-inflammation index (SII), the systemic inflammatory response index (SIRI), the platelet-to-lymphocyte ratio (PLR), the lymphocyte-to-monocyte ratio (LMR), the prognostic nutritional index (PNI), and the geriatric nutritional risk index (GNRI). Statistically significant positive correlations were observed between NLR, dNLR, SII, SIRI, and PLR and the pathological stage of the tumor. We observed statistically significant inverse correlations for LMR, PNI, and GNRI with the tumor stage. SIRI was identified as an independent predictor of the presence of LVI. dNLR was identified as an independent predictor of positive surgical margins. GNRI was identified as an independent predictor of the presence of metastases in the lymph nodes. We noticed the predictive value of SIRI, dNLR, and GNRI in the pathology of bladder cancer patients.

Combined use of CA125, neutrophil/lymphocyte ratio and platelet/lymphocyte ratio for the diagnosis of borderline and malignant epithelial ovarian tumors

BACKGROUND

The mortality rate of ovarian cancer ranks first among three common gynecological malignant tumors due to insidious onset and lack of effective early diagnosis methods. Borderline epithelial ovarian tumor (BEOT) is a type of low malignant potential tumor that is typically associated with better outcomes than ovarian cancer. However, BEOTs are easily confused with benign and malignant epithelial ovarian tumors (EOTs) due to similar clinical symptoms and lack of specific tumor biomarkers and imaging examinations. Notably, a small subset of BEOTs will transform into low-grade serous ovarian carcinoma with a poor prognosis. Therefore, searching for potential biomarkers that can be easily obtained and accurately identify malignant epithelial ovarian tumors (MEOTs) as well as BEOTs is essential for the clinician. Cancer antigen 125 (CA125) is a commonly used biomarker for the diagnosis of EOTs in the preoperative scenario but has low sensitivity and specificity. Nowadays, inflammatory biomarkers including inflammatory cell counts and derived ratios such as neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have been proved to be associated with tumor progression and poor prognosis, and were considered to be the most economically potential surrogate biomarkers for various malignancies. The purpose of this study was to find appropriate combinations of inflammatory and tumor biomarkers to improve the diagnostic efficiency of EOTs, especially the BEOTs.

RESULTS

CA125, NLR and PLR increased steadily among benign, borderline and malignant EOTs and tended to be higher in advanced (stage III-IV) and lymph node metastasis MEOT groups than in early stage (stage I-II) and non-lymph node metastasis MEOT groups. CA125, NLR and PLR could be used separately in the differentiation of EOTs but could not take into account both sensitivity and specificity. The combined use of CA125, NLR and PLR was evaluated to be more efficient, especially in the identification of BEOTs, with both high sensitivity and high specificity.

CONCLUSIONS

The levels of CA125, NLR and PLR were closely related to the nature of EOTs and malignant progression of MEOTs. The combination of CA125, NLR and PLR was more accurate in identifying the nature of EOTs than either alone or double combination, especially for BEOTs.

Independent predictive value of blood inflammatory composite markers in ovarian cancer: recent clinical evidence and perspective focusing on NLR and PLR

Ovarian cancer (OC) is one of the deadliest malignant tumors affecting women worldwide. The predictive value of some blood inflammatory composite markers in OC has been extensively reported. They can be used for early detection and differential diagnosis of OC and can be used for predicting survival, treatment response, and recurrence in the affected patients. Here, we reviewed the predictive values of composite inflammatory markers based on complete blood count, namely neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio, and systemic inflammation index and markers based on blood protein, namely C-reactive protein-to-albumin ratio and prognostic nutritional index in OC, with a focus on NLR and PLR. We referred to the clinical studies on these six markers, reviewed the patient population, and summarized the marker cut-off values, significance, and limitations of these studies. All these studies were retrospective and most of them were single-center clinical studies with small sample sizes. We found that the cut-off values of these markers have not been unified, and methods used to determine these values varied among studies. The predictive value of these markers on survival was mainly reflected in the postoperative patients of multiple subtypes of ovarian cancer including epithelial OC, high-grade serous ovarian carcinoma, and ovarian clear cell carcinoma. We focused on NLR and PLR and calculated their pooled hazard ratios. NLR and PLR were reliable in predicting overall and progression-free survivals in patients with OC. Therefore, it is necessary to adjust important confounding factors and conduct a long-term follow-up prospective cohort study to further clarify the cut-off values of NLR and PLR and their clinical applications.

Progress in Applicability of Scoring Systems Based on Nutritional and Inflammatory Parameters for Ovarian Cancer

Ovarian cancer is a malignancy that seriously endangers women’s health; its case fatality rate ranks first among the gynecological malignancies. The status of nutrition of ovarian cancer patients is related to their prognoses. Thus, it is important to evaluate, monitor, and improve the nutritional status of ovarian cancer patients during their treatment. Currently, there are several tools for examining malnutrition and nutritional assessment, including NRI (nutrition risk index), PG-SGA (patient-generated subjective global assessment), and NRS 2002 (nutritional risk screening 2002). In addition to malnutrition risk examination and related assessment tools, the evaluation of muscle mass, C-reactive protein, lymphocytes, and other inflammation status indicators, such as neutrophils to lymphocytes ratio, lymphocyte-to-monocyte ratio, and C-reactive protein-albumin ratio, is of great importance. The nutritional status of ovarian cancer patients undergoing surgery affects their postoperative complications and survival rates. Accurate evaluation of perioperative nutrition in ovarian cancer patients is crucial in clinical settings. An intelligent nutritional diagnosis can be developed based on the results of its systematic and comprehensive assessment, which would lay a foundation for the implementation of personalized and precise nutritional therapy.

Albumin-Derived NLR Score is a Novel Prognostic Marker for Esophageal Squamous Cell Carcinoma

BACKGROUND

Multidisciplinary treatment for esophageal squamous cell carcinoma (ESCC) has improved outcomes, but the prognosis for ESCC remains poor. Nutritional and inflammatory indicators are reported to be associated with cancer prognosis. The combination of albumin and the derived neutrophil-to-lymphocyte ratio (Alb-dNLR) score was established to measure the immune system and nutritional status. The authors hypothesized that the Alb-dNLR score could be a new reliable prognostic factor for ESCC patients.

METHODS

The study evaluated 269 patients who underwent esophagectomy between April 2010 and March 2018, including 185 patients who received neoadjuvant chemotherapy. The Alb-dNLR score was calculated using serum albumin and the dNLR. The dNLR was calculated as neutrophils to (leukocyte-neutrophil count). The cutoff values of the albumin and dNLR for overall survival (OS) were determined using the receiver operating characteristic curve. Patients were divided into "high" and "low" groups according to the Alb-dNLR score.

RESULTS

A high Alb-dNLR score was found in 61 cases (22.7%). The 5-year OS was 34% in the high Alb-dNLR group and 66.2% in the low Alb-dNLR group (p < 0.0001). The 5-year cause-specific survival (CSS) was 51.5% in the high Alb-dNLR group and 74.7% in the low Alb-dNLR group (p < 0.0001). Multivariate analyses demonstrated that the Alb-dNLR score was an independent prognostic factor for OS (hazard ratio [HR], 2.198; 95% confidence interval [CI], 1.460-3.263; p = 0.0002) and CSS (HR, 1.733; 95% CI, 1.035-2.835; p = 0.0371).

CONCLUSIONS

The Alb-dNLR score is an extremely useful, easy-to-use parameter to predict OS and CSS for ESCC patients.

Neutrophil-to-lymphocyte ratio and chemotherapy response score as prognostic markers in ovarian cancer patients treated with neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is the recommended approach in patients with advanced epithelial ovarian cancer (EOC). However, most patients eventually relapse despite the initial high response rate to chemotherapy. Neutrophil-to-lymphocyte ratio is a well-known biomarker that reflects severe inflammation, critical illness, and mortality in various diseases. Chemotherapy response score (CRS) and neutrophil-to-lymphocyte ratio (NLR) have been identified as potential biomarkers of platinum resistance and disease prognosis. We retrospectively evaluated 132 patients with stage IIIc or IV ovarian/fallopian tube/primary peritoneal cancer who had received NACT followed by IDS from 01/01/2003 to 31/12/2018. CRS was assessed on omental specimens collected from IDS according to ICCR guidelines.

RESULTS

Median age was 64.57 years (SD: 9.72; range 39.2-87.1). Most ovarian tumors were serous epithelial (90.9%; 120/132). An elevated NLR (defined as > 3) was observed in 72% (95/132) of patients in contrast with 28% (37/132) of patients characterized by low NLR status. Median PFS (mPFS) and median overall survival (mOS) were 13.05 months (95% CI: 11.42-14.67)) and 34.69 months (95% CI: 23.26-46.12) respectively. In univariate analysis, CRS3 score was significantly associated with prolonged mPFS (CRS1/2: 12.79 months vs CRS3: 17.7 months; P = 0.008). CRS score was not associated with mOS (P = 0.876). High NLR was not significantly associated with mPFS (P = 0.128), however it was significantly associated with poor mOS (P = 0.012). In multivariate analysis, only performance of surgery maintained its statistical significance with both PFS (P = 0.001) and OS (P = 0.008).

CONCLUSION

NLR could serve as a useful predictor of OS but not PFS in ovarian cancer patients receiving NACT. In accordance with our previous study, CRS score at omentum was found to be associated with PFS but not OS in ovarian cancer patients treated with NACT and IDS.

Role of Systemic Inflammatory Reaction in Female Genital Organ Malignancies - State of the Art

Systemic inflammatory reaction (SIR) is an unfavorable prognostic factor in many malignancies and has a role in all stages of the neoplastic process: initiation, promotion, and disease progression. Analysis of SIR can be performed by assessing indicators (eg, lymphocyte-to-neutrophil, platelet-to-lymphocyte, and monocyte-to-neutrophil ratios) and products of neutrophils and lymphocytes (ie, the systemic immune-inflammation index), or by examining the relationship between levels of C-reactive protein and albumin (based on the Glasgow Prognostic Score, modified Glasgow Prognostic Score, and C-reactive protein-to-albumin ratio). Risk stratification is essential in the clinical management of cancer; hence, the evaluation of these factors has potential applications in the clinical management of patients with cancer and in the development of new therapeutic targets. This review summarizes the current knowledge on SIR indicators and presents their clinical utility in malignancies of the female genital organs.

Predictability of early changes in derived neutrophil-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in patients with advanced non-small cell lung cancer treated with immune checkpoint inhibitors

Background

As association between systemic inflammation and disease progression has been suggested, early changes in neutrophil-to-lymphocyte ratio (NLR) and derived NLR (dNLR) may have accurate predictability for prognosis in non-small cell lung cancer (NSCLC) treated with ICI therapy.

Methods

Complete blood count (CBC) was measured immediately before the first and second cycles of ICI therapy in patients with advanced NSCLC. Differences in NLR and dNLR were measured. When the increase in NLR was ≥1, the patient was classified into the increased NLR group. Similarly, when the increase in dNLR was ≥1, the patient was classified into the increased dNLR group; otherwise, they were classified into the non-increased NLR or dNLR group.

Results

A total of 89 patients was selected for evaluation. Median progression-free survival (PFS) was significantly shorter in the increased NLR group than in the non-increased NLR group (2.6 vs. 9.5 months, P<0.001). The increased dNLR group showed significantly shorter median PFS than the non-increased dNLR group (4.2 vs. 9.2 months, P=0.001). Association with PFS was analyzed using the Cox regression model. In model 1, increase ≥1 in NLR showed significant association (HR =3.085, 95% CI, 1.657–5.742, P<0.001). In model 2, increase ≥1 in dNLR showed significant association (HR =2.826, 95% CI, 1.436–5.561, P=0.003).

Conclusions

Early changes in dNLR were shown to have prognostic value in patients undergoing immunotherapy. It can be an accurate and a comprehensive biomarker for predicting ICI response.

CircRNA hsa_circ_0013958 may contribute to the development of ovarian cancer by affecting epithelial-mesenchymal transition and apoptotic signaling pathways

BACKGROUND

CircRNA plays an important role in the development of tumors, but its mechanism of action in ovarian cancer is still unclear.

METHODS

The expression level of hsa_circ_0013958 in 45 pairs of ovarian cancer tissues and cells was quantified by qRT-PCR, further revealing whether it is related to clinicopathological features and diagnostic value. Next, the effects of hsa_circ_0013958 on the proliferation, migration, invasion, and apoptosis of A2780 and OVCAR-3 cells were detected by CCK-8 assay, Transwell assay, and flow cytometry, respectively. Last, the expression levels of epithelial-mesenchymal transition-related proteins (E-cadherin and Vimentin) and apoptosis-related proteins (Bcl-2 and Bax) were detected by Western blotting.

RESULTS

Hsa_circ_0013958 was highly expressed in ovarian cancer tissues and cells, and its expression was closely related to patient FIGO stage and lymph node metastasis. Further, in vitro studies showed that knockdown of hsa_circ_0013958 suppressed proliferation, migration, and invasion of ovarian cancer cells but elevated the cell apoptotic rate. The expression levels of both epithelial-mesenchymal transition-related proteins and apoptosis-related proteins were also changed.

CONCLUSIONS

Hsa_circ_0013958 may contribute to the development of ovarian cancer by affecting epithelial-mesenchymal transition and apoptotic signaling pathways.

Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

Epithelial ovarian cancer (OC) is the most deadly cancer of the female reproductive system. To date, there is no effective screening method for early detection of OC and current diagnostic armamentarium may include sonographic grading of the tumor and analyzing serum levels of tumor markers, Cancer Antigen 125 (CA-125) and Human epididymis protein 4 (HE4). Microorganisms (bacterial, archaeal, and fungal cells) residing in mucosal tissues including the gastrointestinal and urogenital tracts can be altered by different disease states, and these shifts in microbial dynamics may help to diagnose disease states. We hypothesized that the peritoneal microbial environment was altered in patients with OC and that inclusion of selected peritoneal microbial features with current clinical features into prediction analyses will improve detection accuracy of patients with OC. Blood and peritoneal fluid were collected from consented patients that had sonography confirmed adnexal masses and were being seen at SIU School of Medicine Simmons Cancer Institute. Blood was processed and serum HE4 and CA-125 were measured. Peritoneal fluid was collected at the time of surgery and processed for Next Generation Sequencing (NGS) using 16S V4 exon bacterial primers and bioinformatics analyses. We found that patients with OC had a unique peritoneal microbial profile compared to patients with a benign mass. Using ensemble modeling and machine learning pathways, we identified 18 microbial features that were highly specific to OC pathology. Prediction analyses confirmed that inclusion of microbial features with serum tumor marker levels and control features (patient age and BMI) improved diagnostic accuracy compared to currently used models. We conclude that OC pathogenesis alters the peritoneal microbial environment and that these unique microbial features are important for accurate diagnosis of OC. Our study warrants further analyses of the importance of microbial features in regards to oncological diagnostics and possible prognostic and interventional medicine.

Diagnostic value of derived neutrophil-to-lymphocyte ratio in patients with ovarian cancer

Background

Inflammation plays an important role in the occurrence and development of cancer. Numerous studies have used the derived neutrophil‐to‐lymphocyte ratio (dNLR) to evaluate prognosis in many types of cancer. However, the relationship between dNLR and ovarian cancer and its value in the differential diagnosis of benign and malignant ovarian tumors remain unknown.

Methods

A total of 262 patients with ovarian cancer, 258 with benign ovarian disease, and 232 healthy controls were included in this study. dNLR was calculated using whole blood cell parameters. Receiver operating characteristic curves were generated to obtain sensitivity, specificity, and area under the ROC curve (AUC) to evaluate the diagnostic values of dNLR.

Results

dNLR was significantly different among the ovarian cancer, benign ovarian disease, and healthy control groups (all P < 0.001). Moreover, there were significant differences in dNLR between patients with early‐stage (I and II) and advanced‐stage (III and IV) disease (P < 0.001). dNLR was positively correlated with stage and carbohydrate antigen‐125 in ovarian cancer. A cutoff value of dNLR ≤2.11 was diagnostic in distinguishing ovarian cancer from benign ovarian disease with AUC of 0.729 (95% confidence interval [CI], 0.689‐0.767; P = 0.0001). A cutoff value of dNLR ≤1.9 was diagnostic in distinguishing ovarian cancer from healthy controls with an AUC of 0.821 (95% CI, 0.784‐0.854; P = 0.0001).

Conclusion

dNLR may be a useful indicator for distinguishing between ovarian cancer and benign ovarian disease and for identifying early and advanced ovarian cancer.