Prognostic evaluation of colorectal cancer using three new comprehensive indexes related to infection, anemia and coagulation derived from peripheral blood

The association of preoperative hematologic parameters with short-term clinical outcomes in rectal cancer: A feature importance analysis

BACKGROUND

Various hematologic parameters have been proposed as prognostic factors in rectal cancer management, but data are conflicting and unclear. This study is designed to investigate the prognostic factor capability of preoperative hematologic parameters with postoperative morbidities and mortality in rectal cancer patients undergoing curative resection.

METHODS

All 200 consecutive rectal cancer patients diagnosed at Ghaem University Hospital from 2017 to 2022 were retrospectively evaluated. The receiver operating characteristic (ROC) curves and machine learning (ML) algorithms of Random Forest, Recursive Feature Elimination, simulated annealing, Support Vector Machine, Decision Tree, and eXtreme Gradient Boosting were administered to investigate the role of preoperative hematologic parameters accompanied by baseline characteristics on three clinical outcomes including surgical infectious complications, recurrence, and death.

RESULTS

The frequency of infectious complications was correlated with the surgical procedure, while tumor recurrence was significantly influenced by T stage and N stage. In terms of mortality, alongside T and N stage, the status of resection margin involvement was significantly correlated. Based on the ROC analysis, the NLR >2.69, MPV ≤9 fL, and PDW ≤10.5 fL were more classified patients to mortality status. Likewise, the PLT >220 109/L, MPV ≤9 fL, PDW ≤10.4 fL, and PLR >13.6 were correlated with recurrence. However, all factors examined in this study were not significant classifiers for the outcome of surgical infectious complications. The results of ML algorithms were also in line with ROC analysis.

CONCLUSION

According to the results of both ROC analysis and ML models, preoperative hematologic parameters are considerable prognostic factors of postoperative outcomes in rectal cancer patients, and are recommended to be monitored by clinicians to prevent unfavorable outcomes.

Nutritional and immune-related indicators-based Nomogram for predicting overall survival of surgical oral tongue squamous cell carcinoma

Oral tongue squamous cell carcinoma (OTSCC) is one of the most aggressive oral tumors. The aim of this study was to establish a nomogram to predict overall survival (OS) of TSCC patients after surgery. 169 TSCC patients who underwent surgical treatments in the Cancer Hospital of Shantou University Medical College were included. A nomogram based on Cox regression analysis results was established and internally validated using bootstrap resampling method. pTNM stage, age and total protein, immunoglobulin G, factor B and red blood cell count were identified as independent prognostic factors to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of pTNM stage, indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected concordance index of nomogram was higher than that of pTNM stage (0.794 vs. 0.665, p = 0.0008). The nomogram also had a good calibration and improved overall net benefit. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (p < 0.0001). The nomogram based on nutritional and immune-related indicators represents a promising tool for outcome prediction of surgical OTSCC.

The Effect of Bilirubin on Clinical Outcomes of Patients With Colorectal Cancer Surgery: A Ten-Year Volume Single-Center Retrospective Study

The current study aimed to evaluate the effect of bilirubin on the outcomes of colorectal cancer (CRC) in patients who underwent radical CRC surgery. The levels of serum bilirubin, including total bilirubin (TBil), direct bilirubin (DBil) and indirect bilirubin (IBil), were divided into higher groups and lower groups according to the median. Multivariate logistic regression was performed to analyze the independent predictors for overall complications and major complications. For TBil, the hospitalization time of the higher TBil group was longer than that of the lower TBil group (p = 0.014 < 0.05). For DBil, the higher DBil group had longer operation times (p < 0.01), more intraoperative bleeding (p < 0.01), longer hospital stays (p < 0.01), and higher rates of overall complications (p < 0.01) and major complications (p = 0.021 < 0.05) than the lower DBil group. For the IBil group, blood loss during operation (p < 0.01) and hospital stays (p = 0.041 < 0.05) in the higher IBil group were lower than those in the lower IBil group. In terms of complications, we found that DBil was an independent predictor for overall complications (p < 0.01, OR = 1.036, 95% CI = 1.014-1.058) and major complications (p = 0.043, HR= 1.355, 95% CI= 1.009-1.820). Higher preoperative DBil increase the risk of complications after primary CRC surgery.

Fashionable, but What is Their Real Clinical Usefulness? NLR, LMR, and PLR as a Promising Indicator in Colorectal Cancer Prognosis: A Systematic Review

The link between inflammation and cancer is still an attractive subject of many studies because systemic inflammatory response has been proven to play a pivotal role in cancer progression and metastasis. The strongest relationship between chronic inflammation and cancer development is observed in colorectal cancer (CRC). The evaluation of ratios derived from the routinely performed inflammatory biomarkers shows limited performances and limited clinical utility when individually used as prognostic factors for patients with CRC. In this review, we would like to summarize the latest knowledge about the diagnostic utility of systemic inflammatory ratios: neutrophil/lymphocyte (NLR), lymphocyte/monocyte (LMR), and platelet/lymphocyte (PLR) in CRC. We focused on the papers that assessed the diagnostic utility of blood cell parameters on the basis of the area under the ROC curve published in the recent 6 years. Identification of biomarkers that are significantly associated with prognostic in cancer would help the selection of patients with a high risk of poor outcomes.

Machine learning for identifying benign and malignant of thyroid tumors: A retrospective study of 2,423 patients

Thyroid tumors, one of the common tumors in the endocrine system, while the discrimination between benign and malignant thyroid tumors remains insufficient. The aim of this study is to construct a diagnostic model of benign and malignant thyroid tumors, in order to provide an emerging auxiliary diagnostic method for patients with thyroid tumors. The patients were selected from the Chongqing General Hospital (Chongqing, China) from July 2020 to September 2021. And peripheral blood, BRAFV600E gene, and demographic indicators were selected, including sex, age, BRAFV600E gene, lymphocyte count (Lymph#), neutrophil count (Neu#), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), red blood cell distribution width (RDW), platelets count (PLT), red blood cell distribution width-coefficient of variation (RDW-CV), alkaline phosphatase (ALP), and parathyroid hormone (PTH). First, feature selection was executed by univariate analysis combined with least absolute shrinkage and selection operator (LASSO) analysis. Afterward, we used machine learning algorithms to establish three types of models. The first model contains all predictors, the second model contains indicators after feature selection, and the third model contains patient peripheral blood indicators. The four machine learning algorithms include extreme gradient boosting (XGBoost), random forest (RF), light gradient boosting machine (LightGBM), and adaptive boosting (AdaBoost) which were used to build predictive models. A grid search algorithm was used to find the optimal parameters of the machine learning algorithms. A series of indicators, such as the area under the curve (AUC), were intended to determine the model performance. A total of 2,042 patients met the criteria and were enrolled in this study, and 12 variables were included. Sex, age, Lymph#, PLR, RDW, and BRAFV600E were identified as statistically significant indicators by univariate and LASSO analysis. Among the model we constructed, RF, XGBoost, LightGBM and AdaBoost with the AUC of 0.874 (95% CI, 0.841-0.906), 0.868 (95% CI, 0.834-0.901), 0.861 (95% CI, 0.826-0.895), and 0.837 (95% CI, 0.802-0.873) in the first model. With the AUC of 0.853 (95% CI, 0.818-0.888), 0.853 (95% CI, 0.818-0.889), 0.837 (95% CI, 0.800-0.873), and 0.832 (95% CI, 0.797-0.867) in the second model. With the AUC of 0.698 (95% CI, 0.651-0.745), 0.688 (95% CI, 0.639-0.736), 0.693 (95% CI, 0.645-0.741), and 0.666 (95% CI, 0.618-0.714) in the third model. Compared with the existing models, our study proposes a model incorporating novel biomarkers which could be a powerful and promising tool for predicting benign and malignant thyroid tumors.

The Elderly Nutritional Index for Geriatric Malnutrition Assessment (ENIGMA): concurrent, construct and predictive validity in an external evaluation cohort of community-dwelling older persons

We previously developed a malnutrition risk index, the Elderly Nutritional Index for Geriatric Malnutrition Assessment (ENIGMA) with good predictive accuracy for mortality risk in an original population cohort (SLAS1). Herein, we further evaluate the concurrent and predictive validity of the ENIGMA construct in an external validation cohort (SLAS-2) of 2824 community-dwelling older adults aged 55+ years. They were assessed on the ENIGMA index, Mini Nutritional Assessment-Short Form (MNA-SF) and the Geriatric Nutritional Risk Index (GNRI), known correlates of malnutrition, and baseline and follow-up functional dependency and 10-year mortality risk. Higher ENIGMA risk categories were significantly associated (P < 0·001) with lower education, living alone, smoking, low physical activity, BMI < 18·5 kg/m², poorer muscle strength and functional mobility, exhaustion, physical frailty, homocysteine, glomerular filtration rate, Hb, red and white blood cell counts, platelets, systemic inflammation indexes, metabolic syndrome, CVD, cognitive impairment and depressive symptoms (Geriatric Depression Scale ≥ 5). ENIGMA scores showed statistically significant (P < 0·001) correlations but low-to-moderate concordance with MNA-SF (r = 0·148, agreement = 45·9 %, kappa = 0·085) and GNRI scores (r = 0·156, agreement = 45·8 %, kappa = 0·096). Controlling for known correlates of malnutrition, only high-risk ENIGMA among the indexes significantly predicted baseline functional dependency (OR = 1·64, 95 % CI 1·01, 2·65) and mortality (hazard ratio = 1·65 (95 % CI 1·04, 2·62). ENIGMA marginally out-performed MNA-SF and GNRI in predicting baseline functional dependency (AUC: 0·625 v. 0·584 v. 0·526), follow-up functional dependency (AUC: 0·594 v. 0·525 v. 0·479) and 10-year mortality risk (AUC: 0·641 v. 0·596 v. 0·595). The concurrent and predictive validity of the ENIGMA construct is replicated in an external evaluation study of community-dwelling older persons.

Longitudinal changes in personalized platelet count metrics are good indicators of initial 3-year outcome in colorectal cancer

BACKGROUND

Platelet count or complete blood count (CBC)-based ratios including lymphocyte-to-monocyte (LMR), neutrophil-to-lymphocyte (NLR), hemoglobin-to-platelet (HPR), red blood cell count distribution width-to-platelet (RPR), and platelet-to-lymphocyte (PLR) ratio are good predictors of colorectal cancer (CRC) survival. Their change in time is not well documented, however.

AIM

To investigate the effect of longitudinal CBC ratio changes on CRC survival and their possible associations with clinicopathological properties, comorbidities, and anamnestic data.

METHODS

A retrospective longitudinal observational study was conducted with the inclusion of 835 CRC patients, who attended at Semmelweis University, Budapest. CBC ratios and two additional newly defined personalized platelet count metrics (pPLT_D and pPLT_S, the platelet counts relative to the measurement at the time of CRC diagnosis and to the one 4-6 wk after tumor removal surgery, respectively) were recorded.

RESULTS

The 835 CRC patients had a total of 4608 measurements (5.52 visits/patient, in average). Longitudinal survival models revealed that the increases/decreases in LMR [hazard ratio (HR): 0.4989, P < 0.0001], NLR (HR: 1.0819, P < 0.0001), HPR (HR: 0.0533, P = 0.0038), pPLT_D (HR: 4.9229, P < 0.0001), and pPLT_S (HR: 4.7568, P < 0.0001) values were poor prognostic signs of disease-specific survival. The same was obtained for all-cause mortality. Most abnormal changes occurred within the first 3 years after the diagnosis of CRC. RPR and PLR had an only marginal effect on disease-specific (P = 0.0675) and all-cause mortality (Bayesian 95% credible interval: 0.90–186.05), respectively.

CONCLUSION

LMR, NLR, and HPR are good metrics to follow the prognosis of the disease. pPLT_D and pPLT_S perform just as well as the former, while the use of RPR and PLR with the course of the disease is not recommended. Early detection of the abnormal changes in pPLT_D, pPLT_S, LMR, NLR, or HPR may alert the practicing oncologist for further therapy decisions in a timely manner.

Predictive Value of High Preoperative Serum Total Protein and Elevated Hematocrit in Patients with Non-Small-Cell Lung Cancer after Radical Resection

BACKGROUND

The relationship between the dynamic alterations of nutritional indexes before and after surgery, and the prognosis of non-small-cell lung cancer (NSCLC) after radical surgery are unclear. Methods: This study enrolled 100 NSCLC patients in stages I-III who received radical surgery. The preoperative and postoperative 6-month levels of nine nutrition-related indicators were assessed in patients. Survival was analyzed using Kaplan-Meier curves as well as Cox regression models.

RESULTS

Patients had better disease-free survival (DFS) with baseline total protein (TP) >76.66 g/L (75% vs. 50%, P = .027), baseline albumin (ALB) >37.7 g/L (60% vs. 26.7%, P = .002), baseline albumin to globulin ratio (AGR) >1.31 (63.5% vs. 40.5%, P = .006), or baseline globulin (GLOB) <31.42 g/L (39.4% vs. 62.7%, P = .037). Moreover, patients with increased hematocrit (HCT) (69.8% vs. 43.9% P = .013) and mean corpuscular volume (MCV) (73.2% vs. 42.4%, P = .014) at the postoperative 6-month examination had superior DFS. Cox proportional hazards regression analyses demonstrated that age >65 years, adenocarcinoma (pathological type), higher baseline TP, and post-surgery elevated HCT independently predicted favorable DFS.

CONCLUSION

Lower baseline TP and decreased postoperative HCT levels are independent predictors of prognosis in NSCLC following radical surgical procedures.

Associations of Complete Blood Count Parameters with Disease-Free Survival in Right- and Left-Sided Colorectal Cancer Patients

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Some complete blood count (CBC) parameters are found to be associated with CRC prognosis. In this study, ninety-seven pretreated CRC patients were included, and the patients were divided into two groups: left-sided and right-sided, depending on the anatomical location of the tumor. Based on clinicopathologic features including tumor budding, disease stages, and tumor anatomical location, levels of CBC parameters were compared, and disease-free survivals (DFS) were determined. There were differences between patients with different tumor budding scores for only three parameters, including red cell distribution width (RDW), numbers of platelets, and mean platelet volume (MPV). Furthermore, numbers of WBCs, monocytes, and MPV in CRC patients with early disease stages were higher than those with advanced stages. However, levels of eosinophil in CRC patients with advanced stages were higher than those with early stages. Depending on the tumor anatomical location, we observed that numbers of red blood cells (RBCs), hemoglobin (Hgb), and hematocrit (Hct) in CRC patients with left-sided tumors were higher than those with right-sided tumors. We found that low levels of MPV were associated with shorter DFS. However, high levels of eosinophils were associated with shorter DFS in all CRC patients. When patients were divided based on the tumor anatomical location, higher levels of MPV, MCHC, and Hgb were associated with better DFS in the left-sided but not right-sided CRC patients. However, left-sided, but not right-sided, CRC patients with high levels of eosinophil and RDW had shorter DFS. Furthermore, right-sided, but not left-sided, CRC patients with high levels of platelets tended to have a shorter DFS. Our data show that MPV and eosinophils could serve as potential prognostic biomarkers in pre-treatment CRC patients, regardless of the tumor anatomical location. Additionally, lower levels of MPV, MCHC, and Hgb, and high levels of eosinophils and RDW could be negative predictive biomarkers in left-sided CRC patients.

Preoperative Lymphocyte-to-Monocyte Ratio in the Prognostication of Advanced Resectable Colon Cancer: a Retrospective Observational Study

Lymphocyte-to-monocyte ratio (LMR) has been reported as a biomarker for predicting the prognosis of colorectal cancer. However, the clinical usefulness of LMR requires detailed research, which can contribute to better therapeutic strategies. A cohort of 554 patients with resectable advanced colon cancer in our institution was analyzed retrospectively. An analysis of stages II and III resectable advanced colon cancer was performed. LMR was useful for predicting overall survival (OS) and relapse-free survival (RFS). The ROC curve revealed an LMR value of 2.77 as a cutoff for OS. A high LMR was an independent prognostic factor and was associated with a high hazard ratio (HR) in all cases for OS (HR = 0.530, 95% confidence interval (CI) = 0.334-0.842, p = 0.007). A high LMR was not an independent prognostic factor in stage II cases but was a predictor with the strongest association with prognosis in patients with stage III cases for OS (HR = 0.383, 95% CI = 0.160-0.915, p = 0.031). LMR is a strong predictor of prognosis in patients with stage III colon cancer and may be useful in postoperative treatment options.

Does delaying curative surgery for colorectal cancer influence long-term disease-free survival? A cohort study

BACKGROUND

Surgical wait list time is a major problem in many health-care systems and its influence on survival is unclear. The aim of this study is to assess the impact of wait list time on long-term disease-free survival in patients scheduled for colorectal cancer resection.

MATERIALS AND METHODS

A prospective study was carried out in patients with colorectal cancer scheduled for surgery at a tertiary care center. Wait list time was defined as the time from completion of diagnostic workup to definitive surgery and divided into 2-week intervals from 0 to 6 weeks. The outcome variables were 2-year and 5-year disease-free survival.

RESULTS

A total of 602 patients, 364 (60.5%) male, median age 73 years (range = 71) were defined. The median wait list time was 28 days (range = 99). Two and 5-year disease-free survival rates were 521 (86.5%) and 500 (83.1%) respectively. There were no differences in 2-year or 5-year disease-free survival for the whole cohort or by tumor stage between wait list time intervals except for AJCC stage II tumors which showed a higher 5-year disease-free survival for the 2-4 and 4-6-week wait list time interval (p = 0.021).

CONCLUSIONS

Time from diagnosis to definitive surgery up to 6 weeks is not associated with a decrease in 2-year or 5-year disease-free survival (DFS) in AJCC stage I through III colorectal cancer patients. These are important findings in the light of the COVID-19 pandemic and offer a window of opportunity for preoperative optimization and prehabilitation.

A Prognostic Model Based on Clinicopathological Features and Inflammation- and Nutrition-Related Indicators Predicts Overall Survival in Surgical Patients With Tongue Squamous Cell Carcinoma

Objectives: It is reported that inflammation- and nutrition-related indicators have a prognostic impact on multiple cancers. Here we aimed to identify a prognostic nomogram model for prediction of overall survival (OS) in surgical patients with tongue squamous cell carcinoma (TSCC). Methods: The retrospective data of 172 TSCC patients were charted from the Cancer Hospital of Shantou University Medical College between 2008 and 2019. A Cox regression analysis was performed to determine prognostic factors to establish a nomogram and predict OS. The predictive accuracy of the model was analyzed by the calibration curves and the concordance index (C-index). The difference of OS was analyzed by Kaplan-Meier survival analysis. Results: Multivariate analysis showed age, tumor node metastasis (TNM) stage, red blood cell, platelets, and platelet-to-lymphocyte ratio were independent prognostic factors for OS, which were used to build the prognostic nomogram model. The C-index of the model for OS was 0.794 (95% CI = 0.729-0.860), which was higher than that of TNM stage 0.685 (95% CI = 0.605-0.765). In addition, decision curve analysis also showed the nomogram model had improved predictive accuracy and discriminatory performance for OS, compared to the TNM stage. According to the prognostic model risk score, patients in the high-risk subgroup had a lower 5-year OS rate than that in a low-risk subgroup (23% vs 49%, P < .0001). Conclusions: The nomogram model based on clinicopathological features inflammation- and nutrition-related indicators represents a promising tool that might complement the TNM stage in the prognosis of TSCC.

Preoperative Albumin-Bilirubin Grade as a Prognostic Predictor in Colorectal Cancer Patients Who Undergo Radical Resection

Purpose

The relationship between liver function and colorectal cancer without liver metastases has not been explored. Therefore, we investigated whether the preoperative albumin-bilirubin grade could predict the prognosis of patients with colorectal cancer (CRC) undergoing radical resection, and we designed a quantifiable predictive model.

Patients and Methods

We retrospectively analyzed data from 284 patients with CRC who underwent radical resection in the Second Affiliated Hospital of the Wenzhou Medical University between January 2011 and January 2016. Patients were divided in two groups according to the calculated cut-off: the high albumin-bilirubin (>-2.48) grade and low albumin-bilirubin (≤-2.48) grade group. Kaplan-Meier curves were constructed to compare the overall survival (OS) between the two groups. Univariate and multivariate analyses were performed to identify the independent risk factors for postoperative complications and OS.

Results

Patients with a high albumin-bilirubin grade (n = 165, 58.1%) had a higher rate of postoperative complications (38.2% versus 17.6%, P < 0.001), especially medical (19.4% versus 6.7%, P = 0.002) and severe complications (1.7% versus 7.3%, P = 0.032). They also had a shorter OS (mean survival time, 47.6 versus 54.3 months, P = 0.005), especially patients with tumor-node-metastasis stage III (42.7 months versus 51.6 months, P = 0.036). Age ≥ 70 years (odds ratio [OR] = 2.22, P = 0.003) and high albumin-bilirubin grade (OR = 2.71, P = 0.001) were independent risk factors for postoperative complications, while age ≥ 70 years (hazard ratio [HR] = 2.65, P < 0.001), high albumin-bilirubin grade (HR = 1.81, P = 0.033), tumor-node-metastasis stage II (HR = 13.83, P = 0.010) and III (HR = 23.66, P = 0.002) were independent risk factors of OS.

Conclusion

Preoperative albumin-bilirubin grade could predict postoperative complications (especially medical and severe complications) and OS in patients with CRC, especially in those with tumor-node-metastasis stage III.

Comparison of the Prognostic Value of Platelet-Related Indices in Biliary Tract Cancer Undergoing Surgical Resection

Purpose

Platelet-related indices, including mean platelet volume (MPV) and plateletocrit (PCT), have been reported as new prognostic factors of overall survival (OS) in many cancers, but not yet in biliary tract cancer (BTC). We intended to assess these indices in predicting OS in BTC patients with the aim to build a new prognostic model for patients with BTC after surgical resection.

Materials and Methods

Survival analysis and time receiver operating characteristic analysis were applied to screen the platelet indices. Univariate and multivariate Cox analyses were used to identify independent prognostic factors and develop a new prognostic model. Harrell’s C-statistics, calibration curves, and decisive curve analysis were used to assess the model.

Results

MPV and platelet distribution width (PDW)/PCT showed the best prognostic accuracy among the platelet indices. In multivariable analysis, factors predictive of poor OS were presence of nodal involvement, Non-radical surgery, poor tumor differentiation, carbohydrate antigen 19-9 > 100 U/mL, MPV > 8.1 fl, and PDW/PCT > 190. The new model was found to be superior to the TNM staging system and our new staging system showed higher discriminative power.

Conclusion

MPV and PDW/PCT have high prognostic value in BTC patients, and the novel staging system based on these two indices showed good discrimination and accuracy compared with the American Joint Committee on Cancer 7th TNM staging system.

Receiver Operating Characteristic Prediction for Classification: Performances in Cross-Validation by Example

The stability of receiver operating characteristic in context of random split used in development and validation sets, as compared to the full models for three inflammatory ratios (neutrophil-to-lymphocyte (NLR), derived neutrophil-to-lymphocyte (dNLR) and platelet-to-lymphocyte (PLR) ratio) evaluated as predictors for metastasis in patients with colorectal cancer, was investigated. Data belonging to patients admitted with the diagnosis of colorectal cancer from January 2014 until September 2019 in a single hospital were used. There were 1688 patients eligible for the study, 418 in the metastatic stage. All investigated inflammatory ratios proved to be significant classification models on both the full models and on cross-validations (AUCs > 0.05). High variability of the cut-off values was observed in the unrestricted and restricted split (full models: 4.255 for NLR, 2.745 for dNLR and 255.56 for PLR; random splits: cut-off from 3.215 to 5.905 for NLR, from 2.625 to 3.575 for dNLR and from 134.67 to 335.9 for PLR), but with no effect on the models characteristics or performances. The investigated biomarkes proved limited value as predictors for metastasis (AUCs < 0.8), with largely sensitivity and specificity (from 33.3% to 79.2% for the full model and 29.1% to 82.7% in the restricted splits). Our results showed that a simple random split of observations, weighting or not the patients with and whithout metastasis, in a ROC analysis assures the performances similar to the full model, if at least 70% of the available population is included in the study.