Independent Predictor Of Cancer-specific Survival Research Articles

Clinical features and prediction of long-term survival after surgery for perihilar cholangiocarcinoma.

The treatment of perihilar Cholangiocarcinoma (pCCA) poses specific challenges not only due to its high perioperative complication rates but also due its dismal long-term prognosis with only a few long-term survivors (LTS) among the patients. Therefore, in this analysis characteristics and predictors of LTS in pCCA patients are investigated. In this single center analysis, patients undergoing curative-intent liver resection for pCCA between 2010 and 2022 were categorized into long-term and short-term survivors (STS) excluding perioperative mortality. Binary logistic regression was used to determine key differences between the groups and to develop a prognostic composite variable. This composite variable was subsequently tested in the whole cohort of surgically treated pCCA patients using Cox Regression analysis for cancer-specific survival (CSS). Within a cohort of 209 individuals, 27 patients were identified as LTS (median CSS = 125 months) and 55 patients as STS (median CSS = 16 months). Multivariable analysis identified preoperative portal vein infiltration (OR = 5.85, p = 0.018) and intraoperative packed red blood cell (PRBC) transfusions (OR = 10.29, p = 0.002) as key differences between the groups. A prognostic composite variable based on these two features was created and transferred into a Cox regression model of the whole cohort. Here, the composite variable (HR = 0.35, p<0.001), lymph node metastases (HR = 2.15, p = 0.001) and postoperative complications (HR = 3.06, p<0.001) were identified as independent predictors of CSS. Long-term survival after surgery for pCCA is possible and is strongly negatively associated with preoperative portal vein infiltration and intraoperative PRBC transfusion. As these variables are part of preoperative staging or can be modulated by intraoperative technique, the proposed prognostic composite variable can easily be transferred into clinical management to predict the oncological outcome of patients undergoing surgery for pCCA.

A prognostic nomogram to predict the cancer-specific survival of patients with initially diagnosed metastatic gastric cancer: a validation study in a Chinese cohort.

Few studies have been designed to predict the survival of Chinese patients initially diagnosed with metastatic gastric cancer (mGC). Therefore, the objective of this study was to construct and validate a new nomogram model to predict cancer-specific survival (CSS) in Chinese patients. We collected 328 patients with mGC from Northern Jiangsu People's Hospital as the training cohort and 60 patients from Xinyuan County People's Hospital as the external validation cohort. Multivariate Cox regression was used to identify risk factors, and a nomogram was created to predict CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), the calibration curve, and the decision curve analysis (DCA) in the training cohort and the validation cohort. Multivariate Cox regression identified differentiation grade (P < 0.001), T-stage (P < 0.05), N-stage (P < 0.001), surgery (P < 0.05), and chemotherapy (P < 0.001) as independent predictors of CSS. Nomogram of chemotherapy regimens and cycles was also designed by us for the prediction of mGC. Thus, these factors are integrated into the nomogram model: the C-index value was 0.72 (95% CI 0.70-0.85) for the nomogram model and 0.82 (95% CI 0.79-0.89) and 0.73 (95% CI 0.70-0.86) for the internal and external validation cohorts, respectively. Calibration curves and DCA also demonstrated adequate fit and ideal net benefit in prediction and clinical applications. We established a practical nomogram to predict CSS in Chinese patients initially diagnosed with mGC. Nomograms can be used to individualize survival predictions and guide clinicians in making therapeutic decisions.

Low Expression of GRIM-19 Correlates with Poor Prognosis in Patients with Upper Urinary Tract Urothelial Carcinoma

Purpose: This study aimed to clarify the expression of a gene associated with Retinoid- Interferon-Induced Mortality-19 (GRIM-19) in Upper Urinary Tract Urothelial Carcinoma (UUTUC) and its prognostic significance for UUTUC patients. Materials and Methods: Immunohistochemical (IHC) staining was used to determine the GRIM-19 expression in 70 paired samples. Progression-Free Survival (PFS) and Cancer-Specific Survival (CSS) were assessed using the Kaplan-Meier method. The independent prognostic factors for PFS and CSS were analyzed by multivariable Cox regression models. Results: IHC staining showed that GRIM-19 expression was significantly decreased in UUTUC, and its cellular location changed from being both cytoplasmic and nuclear to only cytoplasmic. Kaplan- Meier analysis revealed that the patients with tumors expressing low GRIM-19 had a significantly higher risk for tumor progression (P = 0.002) and cancer-specific mortality (P &lt; 0.001) compared to those with high GRIM-19 levels. The Cox regression showed that both GRIM-19 expression (P = 0.025) and lymph node metastasis (LN) (P = 0.007) were independent predictors of progression in the muscle-invasive (MIC) subgroup. GRIM-19 expressions (entire cohort: P = 0.011; MIC subgroup: P = 0.025), LN (entire cohort: P = 0.019; MIC subgroup: P = 0.007), and progression (entire cohort: P &lt; 0.001; MIC subgroup: P &lt; 0.001) were independent predictors of cancer-specific survival. Conclusion: Low expression of GRIM-19 in patients with UUTUC had significantly shorter PFS or CSS compared to those with high GRIM-19-expressing tumors. High GRIM-19 expression was also strongly associated with longer PFS in MIC patients. It indicates that GRIM-19 might serve as a promising prognostic biomarker for UUTUC patients.

Association of preoperative sarcopenia with the long-term prognosis of patients with bladder cancer undergoing radical cystectomy

PurposeThis retrospective study aimed to assess the correlation between preoperative sarcopenia and long-term oncologic outcomes in patients undergoing radical cystectomy for bladder cancer.MethodsWe included 528 patients who underwent radical cystectomy for bladder cancer between 2000 and 2010 at Asan Medical Center, Seoul, Korea. Preoperative skeletal muscle mass was quantified by analyzing computed tomography images at the third lumbar vertebra. Sarcopenia was defined based on the skeletal muscle index. We evaluated various clinical and pathological factors to analyze the association between sarcopenia and long-term oncologic outcomes.ResultsThe median follow-up time was 104 months. Sarcopenia was identified in 37.9% of the patients. Although no significant differences were observed in traditional pathological factors between the sarcopenic and non-sarcopenic groups, sarcopenia was significantly associated with worse oncologic outcomes. Compared to the non-sarcopenic groups, the sarcopenic group had lower overall survival rates (52.0% vs. 67.1% at 5 years, 35.5% vs. 52.7% at 10 years) and higher cancer-specific mortality (63.3% vs. 74.3% at 5 years, 50.7% vs. 67.4% at 10 years). Multivariable Cox regression analysis demonstrated that sarcopenia was an independent predictor of cancer-specific survival (hazard ratio: 1.49, 95% confidence interval: 1.11–2.01, p = 0.008), alongside body mass index, tumor stage, lymph node metastasis, and lymphovascular invasion.ConclusionSarcopenia was significantly associated with poor cancer-specific survival in patients undergoing radical cystectomy for bladder cancer. Detecting sarcopenia may assist in preoperative risk stratification and long-term management after radical cystectomy.

Serum α-hydroxybutyrate dehydrogenase as a biomarker for predicting survival outcomes in patients with UTUC after radical nephroureterectomy.

We aimed to determine the prognostic value of α-hydroxybutyrate dehydrogenase (α-HBDH) in upper tract urothelial carcinoma (UTUC) patients after radical nephroureterectomy (RNU). We retrospectively enrolled the data of 544 UTUC patients at West China Hospital from May 2003 to June 2019. Cancer-specific survival (CSS) was the endpoint of interest. The optimal cutoff value of α-HBDH was identified by X-Tile program. After propensity score matching (PSM), we utilized Kaplan‒Meier curves to estimate survival and Cox proportional hazard model for risk assessment. A nomogram was built based on the results of multivariate analysis, and calibration curve, time-dependent receiver operating characteristic (ROC) curves and decision curve analysis were also performed to evaluate the predictive accuracy. Overall, 394 and 150 patients were divided into the α-HBDH-low group and α-HBDH -high group at the cutoff value of 158 U/L, respectively. After PSM, the two groups were well matched for all confounding factors. High α-HBDH was associated with inferior CSS (P = 0.006), and preoperative α-HBDH was an independent predictor for CSS (HR: 1.36; 95% CI:1.08, 1.80), especially in localized UTUC patients (HR: 2.04; 95% CI:1.11, 3.74). Furthermore, the nomogram based on α-HBDH achieved great predictive ability for CSS with areas under the curves of 0.800 and 0.778 for 3-year and 5-year CSS, respectively. Serum α-HBDH was a novel and reliable biomarker for predicting survival outcomes in UTUC patients after RNU but should be further explored.

Development and evaluation of nomograms and risk stratification systems to predict the overall survival and cancer-specific survival of patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and patients with HCC have a poor prognosis and low survival rates. Establishing a prognostic nomogram is important for predicting the survival of patients with HCC, as it helps to improve the patient’s prognosis. This study aimed to develop and evaluate nomograms and risk stratification to predict overall survival (OS) and cancer-specific survival (CSS) in HCC patients. Data from 10,302 patients with initially diagnosed HCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Patients were randomly divided into the training and validation set. Kaplan–Meier survival, LASSO regression, and Cox regression analysis were conducted to select the predictors of OS. Competing risk analysis, LASSO regression, and Cox regression analysis were conducted to select the predictors of CSS. The validation of the nomograms was performed using the concordance index (C-index), the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Net Reclassification Index (NRI), Discrimination Improvement (IDI), the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analyses (DCAs). The results indicated that factors including age, grade, T stage, N stage, M stage, surgery, surgery to lymph node (LN), Alpha-Fetal Protein (AFP), and tumor size were independent predictors of OS, whereas grade, T stage, surgery, AFP, tumor size, and distant lymph node metastasis were independent predictors of CSS. Based on these factors, predictive models were built and virtualized by nomograms. The C-index for predicting 1-, 3-, and 5-year OS were 0.788, 0.792, and 0.790. The C-index for predicting 1-, 3-, and 5-year CSS were 0.803, 0.808, and 0.806. AIC, BIC, NRI, and IDI suggested that nomograms had an excellent predictive performance with no significant overfitting. The calibration curves showed good consistency of OS and CSS between the actual observation and nomograms prediction, and the DCA showed great clinical usefulness of the nomograms. The risk stratification of OS and CSS was built that could perfectly classify HCC patients into three risk groups. Our study developed nomograms and a corresponding risk stratification system predicting the OS and CSS of HCC patients. These tools can assist in patient counseling and guiding treatment decision making.

Establishment and Validation of Prognostic Nomograms for Patients with Metastatic Pulmonary Large Cell Neuroendocrine Carcinoma.

Metastatic pulmonary large cell neuroendocrine carcinoma (LCNEC) is an aggressive cancer with generally poor outcomes. Effective methods for predicting survival in patients with metastatic LCNEC are needed. This study aimed to identify independent survival predictors and develop nomograms for predicting survival in patients with metastatic LCNEC. We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, identifying patients with metastatic LCNEC diagnosed between 2010 and 2017. To find independent predictors of cancer-specific survival (CSS), we performed Cox regression analysis. A nomogram was developed to predict the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC. The concordance index (C-index), area under the receiver operating characteristic (ROC) curves (AUC), and calibration curves were adopted with the aim of assessing whether the model can be discriminative and reliable. Decision curve analyses (DCAs) were used to assess the model's utility and benefits from a clinical perspective. This study enrolled a total of 616 patients, of whom 432 were allocated to the training cohort and 184 to the validation cohort. Age, T staging, N staging, metastatic sites, radiotherapy, and chemotherapy were identified as independent prognostic factors for patients with metastatic LCNEC based on multivariable Cox regression analysis results. The nomogram showed strong performance with C-index values of 0.733 and 0.728 for the training and validation cohorts, respectively. ROC curves indicated good predictive performance of the model, with AUC values of 0.796, 0.735, and 0.736 for predicting the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC in the training cohort, and 0.795, 0.801, and 0.780 in the validation cohort, respectively. Calibration curves and DCAs confirmed the nomogram's reliability and clinical utility. The new nomogram was developed for predicting CSS in patients with metastatic LCNEC, providing personalized risk evaluation and aiding clinical decision-making.

Assessment of Ki-67 proliferation index in prognosis prediction in patients with nonmetastatic clear cell renal cell carcinoma and tumor thrombus

PurposeTo determine the optimal cut-off value of Ki-67 for predicting the survival of patients with clear cell renal cell carcinoma (ccRCC) and tumor thrombus and to explore the correlation between Ki-67 expression and pathological features. Patients and MethodsWe retrospectively analyzed Ki-67 immunohistochemical staining of ccRCC and tumor thrombus resected from February 2006 to February 2022. The survival rate was evaluated using the Kaplan-Meier method. The optimal cut-off value of the Ki-67 expression for predicting survival was determined by the minimum P-value method. Clinicopathological data were compared based on Ki-67 status (low versus high expression). Univariate and multivariate Cox regression analysis was used to explore independent predictors. ResultsA total of 202 patients (median age, 58 years [IQR, 52–65 years], 147 men) with ccRCC and tumor thrombus were included in the study. The optimal cut-off value of Ki-67 for predicting survival was 30%. 159 (78.7%) and 43 (21.3%) patients were included in the low-expression and high-expression groups. Patients with Ki-67 high expression had significantly worse recurrence-free survival (P < 0.001) and cancer-specific survival (P < 0.001). Ki-67 high expression was associated with adverse pathological features, including tumor necrosis, ISUP nuclear grade, sarcomatoid differentiation, perirenal fat invasion, renal pelvis invasion, and inferior vena cava wall invasion (all P < 0.050). Ki-67 expression ≥ 30% (P = 0.016), tumor side (P = 0.003), diabetes (P = 0.040), blood loss (P = 0.016), inferior vena cava wall invasion (P = 0.016), and sarcomatoid differentiation (P = 0.014) were independent predictors of cancer-specific survival. ConclusionThe optimal cut-off level of Ki-67 in predicting the prognosis of ccRCC and tumor thrombus was 30%. The high expression of Ki-67 was associated with the aggressive pathological phenotype and poor prognosis.

Clinicopathological Features and Survival Trends of Non-Epithelial Ovarian Cancer: Analysis of the Surveillance, Epidemiology, and End Results (SEER) Database

Introduction: Owing to their low incidence, no reliable statistics about prognostication derived from large sample sizes have been reported of malignant ovarian germ cell tumors (MOGCTs) and sex cord-stromal tumors (SCSTs). The present study aimed to investigate the clinicopathological prognostic factors and the survival trends of MOGCTs and SCSTs. Materials and Methods: Patients with MOGCTs and SCSTs were recorded in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed between 2000 and 2019. Clinical, demographic, and treatment characteristics were compared between groups of MOGCTs and SCSTs. Cox risk regression analysis and Kaplan-Meier survival curves were used to compare overall survival (OS) and cancer-specific survival (CSS) and to assess the prognostic factors. Results: Information about 2,506 patients with MOGCTs and 1,556 patients with SCSTs was extracted from the SEER database, respectively. Aged <40 years and single were more common in patients with MOGCTs than in those with SCSTs. The vast majority of patients with MOGCTs and SCSTs underwent surgery (98.1% vs. 94.5%; p < 0.001), and women with MOGCTs were more likely to receive chemotherapy than women with SCSTs (56.1% vs. 32.2%; p < 0.001). For both patients before and after propensity-score matching, the 5-year OS rates of patients with SCSTs were lower than those of patients with MOGCTs (p < 0.05). In multivariate Cox regression analysis, both age and surgery were independent predictors of OS in patients with MOGCTs and SCSTs. FIGO staging was an independent predictor of CSS in MOGCT patients. Tumor size and chemotherapy were also independent predictors of CSS in patients with SCSTs. Conclusion: Compared to patients with SCSTs, those with MOGCTs tended to be younger and had a higher OS and CSS. Adjuvant chemotherapy after surgery did not prolong OS and CSS in patients with SCSTs.

Clinicopathological characteristics, surgical treatments, and oncological outcomes of localized primary unifocal urothelial carcinoma involving the ureterovesical junction.

To investigate clinicopathological characteristics, surgical treatments, and oncological outcomes of patients with localized primary unifocal urothelial carcinoma involving the ureterovesical junction (UC-UVJ). Localized primary unifocal UC-UVJ cases in patients admitted to our hospital from March 2013 to August 2021 were reviewed. Clinicopathological parameters, perioperative data, and oncological outcomes were compared between patients grouped by tumor location and surgical treatment. A total of 130 patients with localized primary unifocal UC-UVJ were enrolled in this study. These included 72 cases of bladder cancer (BC) involving the ureteral orifice, and 58 cases of upper urinary tract urothelial carcinoma (UTUC) involving the intramural ureter. The proportion of male patients, hydronephrosis, flank pain/abdominal pain, and tumor size differed significantly between the BC and UTUC groups (all P < 0.05). During the median follow-up period of 32.9months, 49 cases (37.7%) recurred and 29 (22.3%) died from urothelial carcinoma (UC), though no statistical difference in recurrence (P = 0.436) or cancer-specific mortality (P = 0.653) was observed between the BC and UTUC groups. Cox proportional hazards regression analysis identified age, tumor grade, and lymphovascular invasion (LVI) as independent predictors of cancer-specific survival (CSS), and sex, T stage, tumor grade, and LVI as independent predictors of recurrence-free survival (RFS). Owing to positional properties, patients with localized primary unifocal UC-UVJ exhibited significant heterogeneity, leading to varied treatment strategies. No statistically significant differences in CSS or RFS were observed between the BC and UTUC groups. Furthermore, age, sex, T stage, tumor grade, and LVI should be carefully considered in clinical practice because of their associations with CSS and RFS.

Searching for prognostic markers for Stage I epithelial ovarian cancer: A role for systemic inflammatory markers.

To determine the prognostic role of systemic inflammatory markers for Stage I epithelial ovarian cancer (EOC). We performed a retrospective, single-center, observational study. We included patients with Stage I EOC cancer undergoing primary surgery between 1993 and 2016. Inflammatory markers were assessed by analyzing blood samples collected at initial diagnosis before EOC surgery. We evaluated these markers' association with disease-free survival (DFS) and cancer-specific survival (CSS). We included 176 women in our study. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) were related to both DFS and CSS in the univariate analysis. In the multivariate Cox analysis, adjuvant chemotherapy (hazard ratio [HR] 0.17, 95% confidence interval [CI] 0.04-0.71, P = 0.02) and SII ≥730 (HR 6.84, 95% CI 1.30-35.9, P = 0.023) were independent predictors of DFS, while FIGO Stage IB-IC (HR 7.91, 95% CI 1.04-59.8, P = 0.04), NLR ≥3 (HR 56.8, 95% CI 7.46-433, P < 0.001) and PLR ≥169 (HR 49.1 95% CI 11.1-217.8, P = 0.005) were independent predictors of CSS. Systemic inflammatory markers are easily obtainable from patients' routine blood analyses and may represent inexpensive and reproducible prognostic markers in early-stage EOC.

Prognostic Value of T-Cell Density in the Tumor Center and Outer Margins in Gastric Cancer

Tumor-infiltrating lymphocytes are associated with the survival of gastric cancer patients. T-cell densities in the tumor and its periphery were previously identified as prognostic T-cell markers for resectable gastric cancer. Immunohistochemistry for 5 T-cell markers, CD3, CD45RO, CD8, FOXP3, and granzyme B was performed on serial sections of N = 251 surgical resection specimens of patients treated with surgery only in the D1/D2 trial. Positive T cells were digitally quantified into tiles of 0.25 mm2 across 3 regions: the tumor center (TC), the inner invasive margin, and the outer invasive margin (OIM). A classification and regression tree model was employed to identify the optimal combination of median T-cell densities per region with cancer-specific survival (CSS) as the outcome. All statistical tests were 2-sided. CD8OIM was identified as the most dominant prognostic factor, followed by FOXP3TC, resulting in a decision tree containing 3 prognostically distinct subgroups with high (Hi) or low (Lo) density of the markers: CD8OIMHi, CD8OIMLo/FOXP3TCHi, and CD8OIMLo/FOXP3TCLo. In a multivariable Cox regression analysis, which included pathological T and N stages, Lauren histologic types, EBV status, microsatellite instability, and type of surgery, the immune subgroups were independent predictors for CSS. CSS was lower for CD8OIMLo/FOXP3TCHi (HR: 5.02; 95% CI: 2.03-12.42) and for CD8OIMLo/FOXP3TCLo (HR: 7.99; 95% CI: 3.22-19.86), compared with CD8OIMHi (P < .0001). The location and density of both CD8+ and FOXP3+ T cells in resectable gastric cancer are independently associated with survival. The combination of CD8OIM and FOXP3TC T-cell densities is a promising stratification factor that should be validated in independent studies.

The Prognostic Impact of Angiolymphatic Invasion in Bladder Urothelial Carcinoma Patients Undergoing Radical Cystectomy

Purpose: The aim of this study was to investigate the association between angiolymphatic invasion (ALI) and bladder cancer in patients who underwent radical cystectomy (RC).Materials and Methods: Multicenter retrospective data from 495 bladder cancer patients who underwent RC between 2007 and 2019 were enrolled in this study. Patients were stratified into 2 groups according to the presence of ALI. The effect of ALI was analyzed by the Kaplan-Meier method and Cox regression hazard models for patients’ cancer-specific survival (CSS), overall survival (OS), and recurrence-free survival (RFS).Results: The median age of the 495 patients in the study was 65 years, with median and mean follow-up durations of 23.3 months and 37.1 months, respectively. ALI was present in 182 patients (36.8%). ALI was significantly associated with worse RFS as well as CSS and OS (p&lt;0.001, p=0.012, and p=0.01, respectively). Adjusting for significant variables, a multivariate analysis showed that tumor stage (over T2) and ALI were independent predictors for CSS, whereas lymph node (LN) metastasis was not. Meanwhile, the adjusted multivariate analysis showed that tumor stage over T2, ALI, LN metastasis, and positive surgical margin were independent predictors for RFS. Otherwise, tumor grade (over grade 2) was not a significant predictor.Conclusions: The presence of ALI was an independent predictor influencing both CSS and RFS.

Treatment outcome after sequential chemotherapy with cisplatin-etoposide, amrubicin and nogitecan in patients with treatment-related pure small-cell neuroendocrine prostate cancer.

This study retrospectively reviewed the clinical characteristics and treatment outcomes of patients with histologically diagnosed treatment-related pure small-cell neuroendocrine prostate cancer. We retrospectively evaluated data for 13 patients with treatment-related neuroendocrine prostate cancer who were diagnosed between May 2015 and February 2022. Standardized systemic therapies of etoposide plus cisplatin (or carboplatin), amrubicin and nogitecan were selected as sequential treatments. Cancer-specific survival and progression-free survival were evaluated as the primary endpoint. The Cox proportional hazards model was used to evaluate the relationships between treatment regimens, clinical variables, cancer-specific survival and progression-free survival. The median cancer-specific survival after diagnosis for all patients was 22.4months (range 1.3-33.4months). The median progression-free survival was 9.3months after first-line etoposide plus cisplatin (or carboplatin) treatment (n=13); 4.2months after second-line amrubicin treatment (n=4); and>15months after third-line nogitecan treatment (n=2). The median progression-free survival after first-line chemotherapy of the liver metastasis (-) group was 10.2months, and that of the (+) group was 5.3months (P=0.015, hazard ratio=11.6, 95% confidence interval=1.01-133.7). No clinicopathological parameters were identified as significant independent predictors of cancer-specific survival in univariate analysis. Sequential chemotherapy with etoposide plus cisplatin (or carboplatin), amrubicin and nogitecan may be helpful for patients with treatment-related pure small-cell neuroendocrine prostate cancer. Early biopsy of metastases and initiation of effective therapy is essential for patients with progressive castration-resistant prostate cancer and low prostate-specific antigen.

Establishment of a Prognostic Nomogram for Cancer-Specific Survival in Patients With Base-of-Tongue Squamous Cell Carcinoma: A Retrospective Study Based on the SEER Database

Background The aim of this retrospective study was to construct and clinically apply a nomogram for cancer-specific survival (CSS) in patients diagnosed with base-of-tongue squamous cell carcinoma (BOTSCC) to predict their survival prognosis. Methods We collected 8448 patients diagnosed with BOTSCC during 2004–2015 from the Surveillance, Epidemiology, and End Results (SEER) database and divided 30% and 70% of them into validation and training cohorts, respectively. We utilized backward stepwise regression in the Cox model to select variables. Predictive variables were subsequently identified from the variables selected above by using multivariate Cox regression. The new survival model was compared with the American Joint Committee on Cancer (AJCC) prognosis model using the following variables: calibration curve, time-dependent area under the receiver operating characteristic curve (AUC), concordance index (C-index), integrated discrimination improvement (IDI), decision-curve analysis (DCA), and net reclassification improvement (NRI). Results A nomogram was established for predicting the CSS probability in patients with BOTSCC. Factors including sex, race, age at diagnosis, marital status, radiotherapy status, chemotherapy status, TNM AJCC stage, surgery status, tumor size, and months from diagnosis to treatment were selected through multivariate Cox regression as independent predictors of CSS. Calibration plots indicated that the model we established had satisfactory calibration ability. The AUC, C-index, IDI, DCA, and NRI results illustrated that the nomogram performed explicit prognoses more accurately than did the AJCC system alone. Conclusion We identified the relevant factors affecting the survival of BOTSCC patients and analyzed the data on patients suffering from BOTSCC in the SEER database. These factors were used to construct a new nomogram to give clinical staff a more-visual prediction model for the 3-, 5-, and 8-year probabilities of CSS for patients newly diagnosed with BOTSCC, thereby aiding clinical decision making.

Prognostic model for predicting overall and cancer-specific survival among patients with superficial spreading melanoma: A SEER based study

Skin malignant melanoma is one of the most aggressive skin tumors. Superficial spreading melanoma (SSM) is the most common histological type, which can originate from different body skin sites, and some patients can still accumulate regional lymph nodes and even have distant metastasis in some cases. This study used the relevant data from the monitoring, epidemiology and results database of the National Cancer Institute database to study the overall survival (OS) and cancer-specific survival (CSS) of SSM patients and established an SSM nomogram to evaluate the prognosis of patients. A total of 13,922 patients were collected from the monitoring, epidemiology and results database of the National Cancer Institute and randomly divided into a training cohort (8353 cases) and a validation cohort (5569 cases). Univariate and multivariate Cox regression analysis were used to determine prognostic factors, and these factors were used to construct OS and CSS nomograms for patients with SSM. Finally, the discrimination and consistency of the nomogram model were evaluated by the consistency index (C-index), area under the curve (AUC) and calibration curve. Multivariate Cox regression analysis suggested that age, sex, tumor site, the American joint committee on cancer T stage and the first primary melanoma were independent predictors of OS and CSS in patients with SSM and that the American joint committee on cancer N stage was also an independent predictor of CSS in patients with SSM. Based on the above prognostic factors, this study constructed a predictive model. The C-index of the model OS and CSS for this training cohort was 0.805 [95% CI: 0.793-0.817] and 0.896 [95% CI: 0.878-0.913], respectively. The AUC values for 1-, 3-, and 5-year OS were 0.822, 0.820, and 0.821, respectively, and the AUC values for CSS were 0.914, 0.922, and 0.893, respectively. The data indicated that both nomograms showed better predictive accuracy. The calibration curves of the training cohort and the validation cohort were in good agreement. The nomogram has superior predictive performance in predicting 1-, 3-, and 5-year OS and CSS prognosis in patients with SSM and can provide a reference for individualized treatment and clinical counseling of SSM.

Adequate Number of Lymph Nodes Sampled May Determine Appropriate Surgical Modality for Early-Stage NSCLC: A Population-Based Real-World Study

BackgroundThe standard surgical procedure for ≤ 2 cm non-small cell lung cancer (NSCLC), including the number of lymph nodes sampled (nLN) and surgical modality, remains controversial. This study was designed to determine the optimal cohort in which sublobectomy could be an alternative to lobectomy. Materials (or Patients) and MethodsPatients from 1998 to 2017 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The optimal cutoff value of nLN was identified using a restrictive cubic spline graph (RCS). Kaplan–Meier analysis was used to determine cancer-specific survival (CSS). The COX proportional hazard regression model was used to identify the influence of clinical and demographic variables on survival, and propensity score matching (PSM) was used to balance differences in baseline characteristics. Finally, we used an external cohort from a single-center medical institution to verify the conclusions drawn from the SEER database. ResultsA total of 6150 patients were included. The sublobectomy subgroup included segmentectomy (308, 5.0%) and wedge resection (1611, 26.2%). The cutoff value for nLN was 7. In the nLN ≥7 subgroup of the PSM cohort, the CSS of segmentectomy and wedge resection was close to that of the lobectomy subgroup (P = .12), whereas in the nLN <7 subgroup, the CSS of the lobectomy subgroup was significantly higher than that of the sublobectomy with P < .001). Surgical methods, nLN, age, sex, and differentiated grade were independent predictors of CSS. External cohort validation: A total of 1106 patients from the Affiliated Jinhua Hospital of Zhejiang University School of Medicine between 2013 and 2020 were included. The grouping criteria were consistent with the SEER database. In the nLN≥7 subgroup, sublobectomy had a survival outcome similar to that of lobectomy (P = .81). ConclusionSublobectomy and nLN < 7 were strongly associated with poorer CSS for early-stage NSCLC. On the premise of nLN ≥ 7, sublobectomy could provide similar survival outcomes to lobectomy for these patients.

Histological variants and lymphovascular invasion in upper tract urothelial carcinoma can stratify prognosis after radical nephroureterectomy.

Patients with histological variants (HV) of bladder cancer have more advanced disease and poorer survival rates than those with pure urothelial carcinoma (UC). Moreover, lymphovascular invasion (LVI) is an important biomarker after RNU in systematic reviews and meta-analyses. Thus, here we investigated the clinical and prognostic impact of HV and LVI in patients with upper tract urothelial carcinoma (UTUC) treated with radical nephroureterectomy (RNU). Data from 223 UTUC patients treated with RNU without neoadjuvant chemotherapy were retrospectively evaluated. We analyzed differences in clinicopathological features and survival rates between patients with pure UC and those with HV. Conditional survival (CS) analysis was performed to obtain prognostic information over time. A total of 32 patients (14.3%) had HV, with the most common variant being squamous differentiation, followed by glandular differentiation. UTUC with HV was significantly associated with advanced pathological T stage (pT ≥ 3), higher tumor grade (G3), and LVI, compared to pure UC (all P < 0.01). Progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS), were all significantly worse in the HV group compared to the pure UC group (all, P < 0.001). In multivariable analysis, HV and LVI were independent predictors of CSS and OS. We classified the patients into three groups using these two predictors: low-risk (neither HV nor LVI), intermediate-risk (either HV or LVI), and high-risk (both HV and LVI). Significant differences in PFS, CSS, and OS rates were found among the 3 groups. In CS analysis, the conditional PFS, CSS, and OS rates at 1, 2, 3, 4, and 5 years improved with increased duration of event-free survival. CS analysis revealed that most progression events occurred within 2 years after RNU, and patients with risk factors had worse PFS at all time points. A risk model using HV and LVI can stratify PFS, CSS, and OS of patients treated with RNU. In addition, CS analysis revealed that HV and LVI were poor prognostic factors over time after RNU.

Individualized conditional survival nomograms for stage I-III early onset colorectal cancer patients.

Conditional survival accounts for the time already survived after surgery and provides additional survival information. The aim was to assess conditional survival in stages I-III early onset colorectal cancer patients and to create nomograms predicting the conditional overall survival and cancer-specific survival after surgery. A total of 7058 patients who underwent surgical resection of early onset colorectal cancer were identified from surveillance, epidemiology and end results database. The formula used for conditional survival calculation was conditional survival(x|y)=S(x+y)/S(x), where S(x) represents the survival at x years. Conditional survival nomograms were then developed to predict the 5-year conditional overall survival and cancer-specific survival. The 5-year overall survival and cancer-specific survival after surgery increases gradually with additional survival time. Race, tumour site, grade, histology, T stage, N stage, lymph node ratio, preoperative carcinoma embryonic antigen level and perineural invasion status were independent predictors of cancer-specific survival, while age and sex were another two independent risk factors for overall survival. The nomograms based on these factors were successfully developed to predict 5-year overall survival and cancer-specific survival given 1-4years already survived. The probability of achieving postoperative 5-year overall survival and cancer-specific survival for early onset colorectal cancer increases gradually with additional time survived. The developed nomograms are fairly valuable and informative in facilitating clinical treatment and follow-up schemes.

Prognostic prediction by a novel integrative inflammatory and nutritional score based on least absolute shrinkage and selection operator in esophageal squamous cell carcinoma.

This study aimed to establish and validate a novel predictive model named integrative inflammatory and nutritional score (IINS) for prognostic prediction in esophageal squamous cell carcinoma (ESCC). We retrospectively recruited 494 pathologically confirmed ESCC patients with surgery and randomized them into training (n = 346) or validation group (n = 148). The least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) regression analysis was initially used to construct a novel predictive model of IINS. The clinical features and prognostic factors with hazard ratio (HRs) and 95% confidence intervals (CIs) grouped by IINS were analyzed. Nomogram was also established to verify the prognostic value of IINS. According to the LASSO Cox PH regression analysis, a novel score of IINS was initially constructed based on 10 inflammatory and nutritional indicators with the optimal cut-off level of 2.35. The areas under the curve (AUCs) of IINS regarding prognostic ability in 1-year, 3-years, and 5-years prediction were 0.814 (95% CI: 0.769-0.854), 0.748 (95% CI: 0.698-0.793), and 0.792 (95% CI: 0.745-0.833) in the training cohort and 0.802 (95% CI: 0.733-0.866), 0.702 (95% CI: 0.621-0.774), and 0.748 (95% CI: 0.670-0.816) in the validation cohort, respectively. IINS had the largest AUCs in the two cohorts compared with other prognostic indicators, indicating a higher predictive ability. A better 5-years cancer-specific survival (CSS) was found in patients with IINS ≤ 2.35 compared with those with IINS > 2.35 in both training cohort (54.3% vs. 11.1%, P < 0.001) and validation cohort (53.7% vs. 18.2%, P < 0.001). The IINS was then confirmed as a useful independent factor (training cohort: HR: 3.000, 95% CI: 2.254-3.992, P < 0.001; validation cohort: HR: 2.609, 95% CI: 1.693-4.020, P < 0.001). Finally, an IINS-based predictive nomogram model was established and validated the CSS prediction (training set: C-index = 0.71 and validation set: C-index = 0.69, respectively). Preoperative IINS is an independent predictor of CSS in ESCC. The nomogram based on IINS may be used as a potential risk stratification to predict individual CSS and guide treatment in ESCC with radical resection.