Independent Prognostic Factor For Cancer-specific Survival Research Articles

Association between 5-item modified frailty index and clinical outcomes in elderly rectal cancer patients after radical surgery

Frailty is a significant factor contributing to an increased risk of adverse clinical outcomes in older cancer patients. This study aims to investigate the impact of the 5-item modified frailty index (mFI) on both short-term and long-term prognosis in elderly rectal cancer patients who underwent radical resection. And, by integrating the 5-item mFI with clinicopathological characteristics, a postoperative severe complications nomogram and a cancer-specific survival (CSS) prediction nomogram were further constructed. Demographic, clinical, and therapeutic data were collected from 1,034 patients aged ≥ 70 years with rectal cancer who underwent proctectomy between 2017 and 2022. Patients were categorized into three groups based on their mFI scores: 318 patients with mFI = 0, 404 patients with mFI = 1, and 312 patients with mFI ≥ 2. Comparisons among these groups revealed that higher 5-item mFI scores were associated with an increased incidence of both overall and severe postoperative morbidity, prolonged recovery times, and elevated total medical costs. Multivariate logistic regression analysis indicated that an mFI score of ≥ 2 [odds ratio = 2.856, 95% confidence interval (CI): 1.542–5.290, P < 0.001] was an independent risk factor for severe postoperative complications. Similarly, in competing risk analysis, the 5-item mFI was identified as an independent prognostic factor for CSS (subdistribution hazard ratio = 2.00, 95% CI: 1.47–2.72, P < 0.001). The postoperative severe complications nomogram and CSS prediction nomogram AUC values were 0.726 and 0.844, respectively, both demonstrating promising predictive capabilities. In conclusion, the 5-item mFI serves as a concise and effective tool for preoperative frailty stratification and for predicting clinical outcomes in elderly rectal cancer patients.

Impact of Small Tumor Size on Prognosis in T3N1 Colon Cancer.

Traditionally, large tumor size is associated with poor survival in colon cancer, but its impact remains limited and controversial. Recently, the impact of small tumor size on prognosis has gained attention. This study aimed to investigate whether small tumor size can be an additional parameter for T3N1 colon cancer prognosis. We retrospectively analyzed 162 consecutive patients with pT3N1 colon cancer between 2010 and 2021. The optimal cutoff value of tumor size was calculated through receiver operating characteristic curve analysis. We evaluated survival through the Kaplan-Meier method, and the risk of prognosis through multivariate Cox models. The optimal cutoff value of tumor size was 45mm. The recurrence rate was significantly higher in tumor size < 45mm than in ≥ 45mm (25.7% vs. 12.0%, p=0.037). Tumor size < 45mm also had lower overall survival (OS), recurrence-free survival (RFS), and cancer-specific survival (CSS) than its counterpart (p=0.03 for all). In multivariate analyses, age ≥ 70years, undifferentiated histological type, and tumor size < 45mm were independent prognostic factors for OS (p=0.025, p=0.001, p<0.04, respectively), whereas tumor size < 45mm was the only independent prognostic factor for RFS (p=0.043). Meanwhile, the independent prognostic factors for CSS were undifferentiated histological type and tumor size < 45mm (p=0.008 for both). Small tumor size is associated with poor prognosis in pT3N1 colon cancer cases. Thus, small tumors potentially have biologically aggressive features.

Prognostic value of lymph node metrics in lung squamous cell carcinoma: an analysis of the SEER database

IntroductionAlthough the Tumor-Node-Metastasis (TNM) staging system is widely used for staging lung squamous cell carcinoma (LSCC), the TNM system primarily emphasizes tumor size and metastasis, without adequately considering lymph node involvement. Consequently, incorporating lymph node metastasis as an additional prognostic factor is essential for predicting outcomes in LSCC patients.MethodsThis retrospective study included patients diagnosed with LSCC between 2004 and 2018 and was based on data from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute. The primary endpoint of the study was cancer-specific survival (CSS), and demographic characteristics, tumor characteristics, and treatment regimens were incorporated into the predictive model. The study focused on the value of indicators related to pathological lymph node testing, including the lymph node ratio (LNR), regional node positivity (RNP), and lymph node examination count (RNE), in the prediction of cancer-specific survival in LSCC. A prognostic model was established using a multivariate Cox regression model, and the model was evaluated using the C index, Kaplan–Meier, the Akaike information criterion (AIC), decision curve analysis (DCA), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI), and the predictive efficacy of different models was compared.ResultsA total of 14,200 LSCC patients (2004–2018) were divided into training and validation cohorts. The 10-year CSS rate was approximately 50%, with no significant survival differences between cohorts (p = 0.8). The prognostic analysis revealed that models incorporating LNR, RNP, and RNE demonstrated superior performance over the TNM model. The LNR and RNP models demonstrated better model fit, discrimination, and reclassification, with AUC values of 0.695 (training) and 0.665 (validation). The RNP and LNR models showed similar predictive performance, significantly outperforming the TNM and RNE models. Calibration curves and decision curve analysis confirmed the clinical utility and net benefit of the LNR and RNP models in predicting long-term CSS for LSCC patients, highlighting their value in clinical decision-making.ConclusionThis study confirms that RNP status is an independent prognostic factor for CSS in LSCC, with predictive efficacy comparable to LNR, with both models enhancing survival prediction beyond TNM staging.

Nomogram based on the log odds of negative lymph node/T stage can predict the prognosis of patients with colorectal cancer: a retrospective study based on SEER database and external validation in China

ObjectivesThis study investigated the prognostic role of log odds of negative lymph node/T stage (LONT) and established a nomogram based on LONT to predict the prognosis in colorectal cancer (CRC)...

Individualised prediction of chemotherapy benefit in early-onset colorectal cancer

PurposesWhether patients with early-onset colorectal cancer (EOCRC) receive chemotherapy has been controversial, so our study aimed to screen patients with EOCRC who benefit from chemotherapy.MethodsA total of 2166 EOCRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were divided into chemotherapy and non-chemotherapy groups, propensity score matching (PSM) was performed to balance the differences between the groups, and the Kaplan–Meier method was used to calculate the cancer-specific survival (CSS) of EOCRC patients. Multifactorial COX regression analysis was used to identify independent prognostic factors for CSS and to construct a nomogram for predicting CSS in EOCRC patients. The overall risk score was calculated based on Nomogram, and EOCRC patients were classified into high-risk and low-risk groups to assess further chemotherapy's therapeutic effect on patients with different risk stratification.ResultsBefore PSM, patients in the chemotherapy group had poorer CSS (p < 0.001). After PSM, there was no significant difference in patient CSS between the two groups (p = 0.057). Independent prognostic factors (Race, Grade, Pathology, AJCC.N, AJCC.M, CEA, Marital. Status) were screened according to multifactorial COX regression analyses and included in the Nomogram predicting CSS in EOCRC patients. A risk stratification system for EOCRC patients was further developed, and the results showed that chemotherapy had no significant effect on CSS in the low-risk group of patients, but in the high-risk group, chemotherapy significantly improved CSS in EOCRC patients.ConclusionsWe developed a clinical risk model by combining different risk factors, which can accurately screen those with high-risk EOCRC for benefit from chemotherapy. For low-risk EOCRC patients, our results did not observe a better survival benefit from chemotherapy, and more prospective studies are needed in the future to prove our conclusions.

A Nomogram for Predicting Cancer-Specific Survival in Young Patients With Advanced Lung Cancer Based on Competing Risk Model.

Young lung cancer is a rare subgroup accounting for 5% of lung cancer. The aim of this study was to compare the causes of death (COD) among lung cancer patients of different age groups and construct a nomogram to predict cancer-specific survival (CSS) in young patients with advanced stage. Lung cancer patients diagnosed between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and stratified into the young (18-45 years) and old (> 45 years) groups to compare their COD. Young patients diagnosed with advanced stage (IVa and IVb) from 2010 to 2015 were reselected and divided into training and validation cohorts (7:3). Independent prognostic factors were identified through the Fine-Gray's test and further integrated to the competing risk model. The area under the receiver operating characteristic curve (AUC), consistency index (C-index), and calibration curve were applied for validation. The proportion of cancer-specific death (CSD) in young patients was higher than that in old patients with early-stage lung cancer (p < 0.001), while there was no difference in the advanced stage (p = 0.999). Through univariate and multivariate analysis, 10 variables were identified as independent prognostic factors for CSS. The AUC of the 1-, 3-, and 5-year prediction of CSS was 0.688, 0.706, and 0.791 in the training cohortand 0.747, 0.752, and 0.719 in the validation cohort. The calibration curves demonstrated great accuracy. The C-index of the competing risk model was 0.692 (95% CI: 0.636-0.747) in the young patient cohort. Young lung cancer is a distinct entity with a different spectrum of competing risk events. The construction of our nomogramcan provide new insights into the management of young patients with lung cancer.

Establishment of nomogram to predict overall survival and cancer-specific survival of local tumor resection in patients with colorectal cancer liver metastasis with unresectable metastases: a large population-based analysis

Background and PurposeThe tumour-node metastasis (TNM) classification is a common model for evaluating the prognostic value of tumour patients. However, few models have been used to predict the survival outcomes of patients with colorectal cancer liver metastasis (CRLM) with unresectable metastases who received the primary local surgery. Thus, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to establish novel nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of these patients.MethodsExtracted primary data on CRLM patients by local surgery from SEER database. All prognostic factors of OS and CSS were determined by Cox regression analysis. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were used to further evaluate the accuracy and discrimination of these nomograms. Decision curve analysis (DCA) was executed to evaluate the nomograms for the clinical net benefit. Risk stratification analysis (RSA) was used to evaluate the reliability of them in clinical.Results3622 eligible patients were screened and assigned to training cohort (1812) or validation cohort (1810). The age, chemotherapy, tumour grade, primary tumour site, tumour size, lymph node positive rate (LNR), marital status, and carcinoembryonic antigen (CEA) were independent prognostic factors of OS. Additionally, the age, chemotherapy, tumour grade, primary tumour site, tumour size, LNR, and CEA were independent prognostic factors of CSS. The results of C-indexes and ROC curves indicated that the established nomograms exhibited better discrimination power than TNM classification. The calibration curves demonstrated excellent agreement between the predicted and actual survival rates for 1-, 3-, and 5 year OS and CSS. Meanwhile, the validation cohort demonstrated similar results. Background the clinic context, the DCA showed that these nomograms have higher net benefits, and the RSA showed that patients were further divided into low risk, medium risk, and high risk groups according to the predicted scores from nomograms. And, the Kaplan–Meier curve and log-rank test showed that the survival differences among the three groups are statistically significant.ConclusionsThe prognostic nomograms showed very high accuracy, identifiability, and clinical practicality in predicting the OS and CSS of CRLM patients with unresectable metastases treated by local surgery at 1-, 3-, and 5 years, which might improve individualized predictions of survival risks and help clinicians formulate treatment plans.

A novel prognostic model of de novo metastatic hormone-sensitive prostate cancer to optimize treatment intensity.

The treatment and prognosis of de novo metastatic hormone-sensitive prostate cancer (mHSPC) vary. We established and validated a novel prognostic model for predicting cancer-specific survival (CSS) in patients with mHSPC using retrospective data from a contemporary cohort. 1092 Japanese patients diagnosed with de novo mHSPC between 2014 and 2020 were registered. The patients treated with androgen deprivation therapy and first-generation anti-androgens (ADT/CAB) were assigned to the Discovery (N = 467) or Validation (N = 328) cohorts. Those treated with ADT and androgen-receptor signaling inhibitors (ARSIs) were assigned to the ARSI cohort (N = 81). Using the Discovery cohort, independent prognostic factors of CSS, the extent of disease score ≥ 2 or the presence of liver metastasis; lactate dehydrogenase levels > 250U/L; a primary Gleason pattern of 5, and serum albumin levels ≤ 3.7g/dl, were identified. The prognostic model incorporating these factors showed high predictability and reproducibility in the Validation cohort. The 5-year CSS of the low-risk group was 86% and that of the high-risk group was 22%. Approximately 26.4%, 62.7%, and 10.9% of the patients in the Validation cohort defined as high-risk by the LATITUDE criteria were further grouped into high-, intermediate-, and low-risk groups by the new model with significant differences in CSS. In the ARSIs cohort, high-risk group had a significantly shorter time to castration resistance than the intermediate-risk group. The novel model based on prognostic factors can predict patient outcomes with high accuracy and reproducibility. The model may be used to optimize the treatment intensity of de novo mHSPC.

Prognostic Influence of Galectin-1 in Gastric Adenocarcinoma.

Galectin-1 (Gal-1), a member of the human lectin family, has garnered attention for its association with aggressive behavior in human tumors, prompting research into the development of targeted drugs. This study aims to assess the staining pattern and prognostic significance of Gal-1 immunohistochemical expression in a homogeneous cohort of Western patients with gastric cancer (GC). A total of 149 cases were included and tissue microarrays were constructed. Stromal Gal-1 expression was observed to some extent in most tumors, displaying a cytoplasmic pattern. Cases with stromal Gal-1 overexpression showed significantly more necrosis, lymphovascular invasion, advanced pTNM stages, recurrences, and cancer-related deaths. Epithelial Gal-1 expression was present in 63.8% of the cases, primarily exhibiting a cytoplasmic pattern, and its overexpression was significantly associated with lymphovascular invasion, peritumoral lymphocytic infiltration, and tumor-related death. Kaplan/Meier curves for cancer-specific survival (CSS) revealed a significantly worse prognosis for patients with tumors exhibiting stromal or epithelial Gal-1 overexpression. Furthermore, stromal Gal-1 expression stratified stage III patients into distinct prognostic subgroups. In a multivariable analysis, increased stromal Gal-1 expression emerged as an independent prognostic factor for CSS. These findings underscore the prognostic relevance of Gal-1 and suggest its potential as a target for drug development in Western patients with GC.

Right-sided versus left-sided colorectal cancer in elderly patients: a sub-analysis of a large multicenter case–control study in Japan

PurposeThis study investigated the impact of sidedness of colorectal cancer (CRC) in elderly patients on the prognosis.MethodsIn a sub-analysis of a multicenter case–control study of CRC patients who underwent surgery at ≥ 80 years old conducted in Japan between 2003 and 2007, both short- and long-term outcomes were compared between right-sided colon cancers (RCCs) and left-sided colorectal cancers (LCCs). RCCs were defined as those located from the cecum to the transverse colon.ResultsAmong the 1680 patients who underwent curative surgery, 812 and 868 had RCCs and LCCs, respectively. RCCs were more frequent than LCCs in those who were female, had renal comorbidities, and had a history of abdominal surgery. Regarding tumor characteristics, RCCs were larger, invaded more deeply, and were diagnosed as either mucinous or signet ring-cell carcinoma more frequently than LCCs. Regarding the prognosis, patients with RCCs had a significantly longer cancer-specific survival (CS-S) and cancer-specific relapse-free survival (CS-RFS) than those with LCCs. Furthermore, sidedness was determined to be an independent prognostic factor for CS-S and CS-RFS.ConclusionRCCs, which accounted for half of the cases in patients ≥ 80 years old, showed better long-term outcomes than LCCs.

Impact of Cytoreductive Nephrectomy in the Management of Metastatic Renal Cell Carcinoma: A Multicenter Retrospective Study.

In this study, we aimed to determine the utility of cytoreductive nephrectomy (CN) in real-world clinical practice and investigate whether CN contributes to improved oncological outcomes in patients with metastatic renal cell carcinoma (mRCC). This retrospective multicenter cohort study enrolled patients with mRCC who received systemic therapy at six institutions between May 2005 and May 2023. The patients were divided into those who did not undergo CN (Group I) and those who underwent CN (Group II). The primary endpoints were oncological outcomes, including cancer-specific survival (CSS) and progression-free survival (PFS). Altogether, 137 patients with mRCC were included in this study. The median CSS was 14 months in Group I and 32 months in Group II (p < 0.001). Additionally, the median PFS in Groups I and II was 5 and 13 months, respectively (p = 0.006). A multivariate analysis showed that CN was an independent prognostic factor for CSS and PFS. Hence, CN is a potential treatment modality that can improve oncological outcomes in patients with mRCC.

Clinicopathological features, prognostic factors, and prognostic survival prediction in patients with extrahepatic bile duct cancer liver metastasis.

Extrahepatic bile duct cancer (EBDC) is a compound malignant tumor mainly consisting of extrahepatic cholangiocarcinoma and gallbladder carcinoma. Most EBDC patients are diagnosed at an advanced stage characterized by distant metastases, and the liver is one of the common sites of metastasis. Hence, the purpose of this study is to investigate the clinicopathological features, identify prognostic risk factors, and assess the long-term prognosis of extrahepatic bile duct cancer liver metastasis (EBDCLM). We identified 1922 eligible EBDCLM patients from the SEER database.Cox regression models were used to predict independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS),and Kaplan-Meier survival curves were drawn. A nomogram was constructed based on the results of multivariate Cox analysis, and the predictive effect of the nomogram was evaluated. Age, surgery, chemotherapy, brain metastasis, and lung metastasis were common independent prognostic factors for OS and CSS, and radiotherapy and bone metastasis were independent prognostic factors for CSS. The Kaplan-Meier survival curves showed a significant increase in survival for patients aged less than or equal to 70 years, undergoing surgery and chemotherapy, and without lung metastases. The results showed that the nomogram constructed by us had good predictability and ha d strong clinical application value. Our study identified age, surgery, chemotherapy, brain metastasis, and lung metastasis as independent prognostic factors for EBDCLM patients. The nomogram can accurately predict the survival probability, which is helpful for clinicians to assess the prognosis of patients with advanced EBDC and provide personalized clinical decisions.

Impact of examined lymph node count on survival outcomes in patients with stage T1-2N0M0 small cell lung cancer undergoing surgery: A retrospective cohort study.

To explore the relationship between the count of examined lymph nodes (ELNs) and survival outcomes in patients with stage T1-2N0M0 small cell lung cancer (SCLC) after surgical treatment. We analyzed data from patients with SCLC in the Surveillance, Epidemiology, and End Results database. The study focused on examining the correlation between the ELN count and both cancer-specific survival (CSS) and overall survival (OS). This relationship was investigated using restricted cubic spline curves within the framework of multivariable Cox regression models. The cutoff value for both CSS and OS was 7 ELN counts. Patients with ELN < 7 had a median CSS of 64 months, significantly lower than 123 months of patients with ELN ≥ 7 (P = .012). Multivariable Cox regression analysis indicated that ELN ≥ 7 was an independent prognostic factor for CSS (hazard ratio = 0.50, 95% confidence interval: 0.30-0.83; P = .007). Similarly, Patients with ELN < 7 had a median OS of 41 months for patients with ELN < 7, compared to 103 months for those with ELN ≥ 7 (P = .004). Multivariable Cox regression analysis confirmed that ELN ≥ 7 was an independent prognostic factor for OS (hazard ratio = 0.54, 95% confidence interval: 0.36-0.81; P = .003). ELN ≥ 7 is recommended as the threshold for evaluating the quality of postoperative lymph node examination and for prognostic stratification in patients with stage T1-2N0M0 SCLC undergoing surgery.

Impact of severe postoperative complications on the prognosis of older patients with colorectal cancer: a two-center retrospective study

BackgroundThe occurrence of postoperative complications may affect short-term outcomes and prognosis of patients with various malignancies. However, the prognostic impact of these complications in older patients with colorectal cancer (CRC) remains unclear. Therefore, this study aimed to investigate the impact of severe postoperative complications on the oncological outcomes of older (aged ≥ 80 years) and non-older (aged < 80 years) patients with CRC.MethodsWe retrospectively analyzed 760 patients with stage I–III CRC who underwent curative surgery in two institutions between 2013 and 2019. The patients were categorized into older (aged ≥ 80 years, 191 patients) and non-older (aged < 80 years, 569 patients) groups. Short- and long-term outcomes were compared between the two groups.ResultsThe incidence of severe postoperative complications did not differ between the two groups (p = 0.981). Cancer-specific survival (CSS) was significantly worse in older patients with severe complications than in those without severe complications (p = 0.007); meanwhile, CSS did not differ between the non-older patients with severe complications and those without severe complications. Survival analysis revealed that the occurrence of severe postoperative complications was an independent prognostic factor for CSS in older patients (hazard ratio = 4.00, 95% confidence interval: 1.27–12.6, p = 0.017).ConclusionCRC surgery can be safely performed in older and non-older patients. Moreover, the occurrence of severe postoperative complications might more strongly affect the prognosis of older patients than that of non-older patients.

Absence of GATA3/FOXA1 co-expression predicts poor prognosis in upper tract urothelial carcinoma.

GATA binding protein 3 (GATA3) and forkhead box A1 (FOXA1) have been individually implicated in the progression of upper tract urothelial carcinoma (UTUC). This study aims to evaluate the prognostic value of GATA3/FOXA1 co-expression in UTUC patients. We collected 108 UTUC pathological tissue samples with complete follow-up data and 24 normal control urothelial tissues. We created a 132-site microarray and performed immunohistochemistry (IHC) to measure GATA3 and FOXA1 expression levels. Kaplan-Meier survival and Cox regression analyses were conducted to assess UTUC prognosis. GATA3 expression was positively correlated with FOXA1 (P=0.031). Absence of GATA3/FOXA1 co-expression (GATA3-/FOXA1-) was associated with tumor extensive necrosis (P=0.001) after Bonferroni correction for multiple comparisons. GATA3-/FOXA1- was associated with shorter Disease-Free Survival (DFS) (P=0.001) and Cancer-Specific Survival (CSS) (P<0.001) than other combination groups. Multivariate analyses identified extensive necrosis as an independent prognostic factor for CSS (P=0.030). Our study revealed a positive correlation between GATA3 and FOXA1 expression in UTUC. GATA3-/FOXA1- is linked to tumor extensive necrosis and poor prognosis in UTUC and may serve as a potential biomarker for UTUC patients.

Prognostic values of tumor size and location in early stage endometrial cancer patients who received radiotherapy.

To investigate the correlation between tumor size, tumor location, and prognosis in patients with early-stage endometrial cancer (EC) receiving adjuvant radiotherapy. Data of patients who had been treated for stage I-II EC from March 1999 to September 2017 in 13 tertiary hospitals in China was screened. Cox regression analysis was performed to investigate associations between tumor size, tumor location, and other clinical or pathological factors with cancer-specific survival (CSS) and distant metastasis failure-free survival (DMFS). The relationship between tumor size as a continuous variable and prognosis was demonstrated by restricted cubic splines. Prognostic models were constructed as nomograms and evaluated by Harrell's C-index, calibration curves and receiver operating characteristic (ROC) curves. The study cohort comprised 805 patients with a median follow-up of 61 months and a median tumor size of 3.0 cm (range 0.2-15.0 cm). Lower uterine segment involvement (LUSI) was found in 243 patients (30.2%). Tumor size and LUSI were identified to be independent prognostic factors for CSS. Further, tumor size was an independent predictor of DMFS. A broadly positive relationship between poor survival and tumor size as a continuous variable was visualized in terms of hazard ratios. Nomograms constructed and evaluated for CSS and DMFS had satisfactory calibration curves and C-indexes of 0.847 and 0.716, respectively. The area under the ROC curves for 3- and 5-year ROC ranged from 0.718 to 0.890. Tumor size and LUSI are independent prognostic factors in early-stage EC patients who have received radiotherapy. Integrating these variables into prognostic models would improve predictive ability.

Establishment and validation of nomogram models for overall survival and cancer-specific survival in spindle cell sarcoma patients

Spindle cell sarcoma (SCS) is rare in clinical practice. The objective of this study was to establish nomograms to predict the OS and CSS prognosis of patients with SCS based on the Surveillance, Epidemiology, and End Results (SEER) database. The data of patients with SCS between 2004 and 2020 were extracted from the SEER database and randomly allocated to a training cohort and a validation cohort. Univariate and multivariate Cox regression analyses were used to screen for independent risk factors for both overall survival (OS) and cancer-specific survival (CSS). Nomograms for OS and CSS were established for patients with SCS based on the results of multivariate Cox analysis. Then, we validated the nomograms by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Finally, Kaplan‒Meier curves and log-rank tests were applied to compare patients with SCS at three different levels and in different treatment groups. A total of 1369 patients with SCS were included and randomly allocated to a training cohort (n = 1008, 70%) and a validation cohort (n = 430, 30%). Age, stage, grade, tumour location, surgery, radiation and diagnosis year were found to be independent prognostic factors for OS by Cox regression analysis, while age, stage, grade, tumour location and surgery were found to be independent prognostic factors for CSS. The nomogram models were established based on the results of multivariate Cox analysis for both OS and CSS. The C-indices of the OS model were 0.76 and 0.77 in the training and validation groups, respectively, while they were 0.76 and 0.78 for CSS, respectively. For OS, the 3- and 5-year AUCs were 0.801 and 0.798, respectively, in the training cohort and 0.827 and 0.799, respectively, in the validation cohort; for CSS, they were 0.809 and 0.786, respectively, in the training cohort and 0.831 and 0.801, respectively, in the validation cohort. Calibration curves revealed high consistency in both OS and CSS between the observed survival and the predicted survival. In addition, DCA was used to analyse the clinical practicality of the OS and CSS nomogram models and revealed that they had good net benefits. Surgery remains the main treatment method for SCS patients. The two nomograms we established are expected to accurately predict the personalized prognosis of SCS patients and may be useful for clinical decision-making.

Analysis of prognostic factors in different grades of histologic differentiation in colorectal cancer patients receiving preoperative neoadjuvant chemotherapy and establishment of prognostic nomograms for moderately differentiated grade.

The aim of this study is to analyze the differences in independent prognostic factors of cancer-specific survival (CSS) and overall survival (OS) in patients with different grades of histologic differentiation of colorectal cancer (CRC) who received preoperative neoadjuvant chemotherapy (NAC) and to establish a nomogram for predicting postoperative survival based on moderately differentiated CRC. We analyzed CRC patients from the SEER database who received NAC before operation between 2010 and 2015. The Kaplan-Meier curves were drawn to describe the differences in CSS and OS of CRC patients with different histologic grades of differentiation. Cox regression analysis was used to determine the independent prognostic factors. Nomograms were established to predict CSS and OS at 3 and 5 years by integrating independent prognostic factors. The calibration curve, receiver operating characteristic (ROC) curve, and C-index were used to verify nomograms. A total of 6481 patients with CRC who received preoperative NAC were included in this study. Patients with different grades of histologic differentiation had significant differences in CSS and OS (P < 0.001), and the independent prognostic factors of different grades of histologic differentiation showed heterogeneity. In patients with moderately differentiated grade CRC, the independent prognostic factors for CSS and OS were age, race, marital status, serum carcinoembryonic antigen (CEA) level before treatment, site of primary tumor, histologic type, pT stage, pN stage, liver metastasis, and lung metastasis. Nomograms were established based on the independent prognostic factors of moderately differentiated grade CRC, and its calibration curves, area under the curve (AUC), and C-index showed good prediction accuracy. The independent prognostic factors of CSS and OS are different in patients with different grades of histologic differentiation of CRC who received NAC before the operation. Nomograms can be used to predict the survival of patients with moderately differentiated grade CRC who received preoperative NAC and to assist clinicians in making clinical decisions.

The clinical predictive value of geriatric nutritional risk index in elderly rectal cancer patients received surgical treatment after neoadjuvant therapy.

The assessment of nutritional status has been recognized as crucial in the treatment of geriatric cancer patients. The objective of this study is to determine the clinical predictive value of the geriatric nutritional risk index (GNRI) in predicting the short-term and long-term prognosis of elderly rectal cancer (RC) patients who undergo surgical treatment after neoadjuvant therapy. Between January 2014 and December 2020, the clinical materials of 639 RC patients aged ≥70 years who underwent surgical treatment after neoadjuvant therapy were retrospectively analysed. Propensity score matching was performed to adjust for baseline potential confounders. Logistic regression analysis and competing risk analysis were conducted to evaluate the correlation between the GNRI and the risk of postoperative major complications and cumulative incidence of cancer-specific survival (CSS). Nomograms were then constructed for postoperative major complications and CSS. Additionally, 203 elderly RC patients were enrolled between January 2021 and December 2022 as an external validation cohort. Multivariate logistic regression analysis showed that GNRI [odds ratio = 1.903, 95% confidence intervals (CI): 1.120-3.233, p = 0.017] was an independent risk factor for postoperative major complications. In competing risk analysis, the GNRI was also identified as an independent prognostic factor for CSS (subdistribution hazard ratio = 3.90, 95% CI: 2.46-6.19, p < 0.001). The postoperative major complication nomogram showed excellent performance internally and externally in the area under the receiver operating characteristic curve (AUC), calibration plots and decision curve analysis (DCA). When compared with other models, the competing risk prognosis nomogram incorporating the GNRI achieved the highest outcomes in terms of the C-index, AUC, calibration plots, and DCA. The GNRI is a simple and effective tool for predicting the risk of postoperative major complications and the long-term prognosis of elderly RC patients who undergo surgical treatment after neoadjuvant therapy.

Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma

BackgroundSeveral researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection. MethodsThe data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC). ResultsThe RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication. ConclusionThe present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.