Independent Prognostic Factor For Cancer-specific Survival Research Articles

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.

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.

This study investigated the impact of sidedness of colorectal cancer (CRC) in elderly patients on the prognosis. In a sub-analysis of a multicenter case-control study of CRC patients who underwent surgery at ≥ 80years 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. Among 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. RCCs, which accounted for half of the cases in patients ≥ 80years old, showed better long-term outcomes than LCCs.

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 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.

Two web-based dynamically interactive nomograms and risk stratification systems for predicting survival outcomes and guiding treatment in non-metastatic nasopharyngeal carcinoma.

A nomogram is a valuable and easily accessible tool for individualizing cancer prognosis. This study aims to establish and validate two prognostic nomograms for long-term overall survival (OS) and cancer-specific survival (CSS) in non-metastatic nasopharyngeal carcinoma (NPC) patients and to investigate the treatment options for the nomogram-based risk stratification subgroups. A total of 3959 patients with non-metastatic NPC between 2004 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly allocated to the training and validation cohorts in a 7:3 ratio. Prognostic nomograms were constructed to estimate OS and CSS by integrating significant variables from multivariate Cox regression employing a backward stepwise method. We examined the correlation indices (C-index) and areas under the curves (AUC) of time-dependent receiver operating characteristic curves to assess the discriminative ability of our survival models. The comprehensive enhancements of predictive performance were evaluated with net reclassification operating improvement (NRI) and integrated discrimination improvement (IDI). Reliability was validated using calibration plots. Decision curve analysis (DCA) was used to estimate clinical efficacy and capability. Finally, the nomogram-based risk stratification system used Kaplan-Meier survival analysis and log-rank tests to examine differences between subgroups. The following independent parameters were significant predictors for OS: sex, age, race, marital status, histological type, median household income, AJCC stage tumor size, and lymph node size. Except for the race variables mentioned above, the rest were independent prognostic factors for CSS. The C-index, AUC, NRI, and IDI indicated satisfactory discriminating properties. The calibration curves exhibited high concordance with the exact outcomes. Moreover, the DCA demonstrated performed well for net benefits. The prognosis significantly differed between low- and high-risk patients (p < 0.001). In a treatment-based stratified survival analysis in risk-stratified subgroups, chemotherapy benefited patients in the high-risk group compared to radiotherapy alone. Radiotherapy only was recommended in the low-risk group. Our nomograms have satisfactory performance and have been validated. It can assist clinicians in prognosis assessment and individualized treatment of non-metastatic NPC patients.

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.

Development and validation of nomograms to recurrence and survival in patients with early-stage cervical adenocarcinoma

PurposeCervical adenocarcinoma is one of the most common types of cervical cancer and its incidence is increasing. The biological behavior and treatment outcomes of cervical adenocarcinoma (CA) differ from those of squamous cell carcinoma (SCC). We sought to develop a model to predict recurrence and cancer-specific survival (CSS) deaths in CA patients.Methods131 patients were included in model development and internal validation, and patients from the SEER database (N = 1679) were used for external validation. Multivariable Cox proportional hazards regression analysis was used to select predictors of relapse-free survival (RFS) and CSS and to construct the model, which was presented as two nomograms. Internal validation of the nomograms was performed using the bootstrap resampling method.ResultsAge, FIGO (International Federation of Gynecology and Obstetrics) stage, size of the tumor, lymph metastasis and depth of invasion were identified as independent prognostic factors for RFS, while age, FIGO stage, size of the tumor and number of positive LNs were identified as independent prognostic factors for CSS. The nomogram of the recurrence model predicted 2- and 5-year RFS, with optimism adjusted c-statistic of 75.41% and 74.49%. Another nomogram predicted the 2- and 5-year CSS with an optimism-adjusted c-statistic of 83.22% and 83.31% after internal validation; and 68.6% and 71.33% after external validation.ConclusionsWe developed and validated two effective nomograms based on static nomograms or online calculators that can help clinicians quantify the risk of relapse and death for patients with early-stage CA.

Comprehensive study of clinical features, prognostic factors, and survival in patients with pancreatic solid pseudopapillary neoplasms based on the 2019 WHO classification.

Pancreatic solid pseudopapillary neoplasms (pSPNs) are a rare tumor type with a limited understanding of their clinical characteristics and survival outcomes. We aimed to investigate potential prognostic factors among the existing clinical features in patients diagnosed with pSPN. For this study, we utilized data from the Surveillance Epidemiology and End Results (SEER) database, specifically selecting patients with a histology type of pSPN from the years 2000 to 2019. Subsequently, we conducted both univariate and multivariate Cox regression analyses in a systematic manner to identify potential prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS) in the selected group of patients. To assess the disparity in OS and CSS among different clinical features and treatments, Kaplan-Meier curves were generated. Furthermore, utilizing the results obtained from the multivariate analysis, we developed a nomogram predictive model to effectively forecast the prognosis of patients diagnosed with pSPN. Calibration plots were presented to demonstrate the predictive accuracy and reliability of the nomogram predictive model. The study comprised a total of 433 participants, with 85.7% of the patients diagnosed with pSPN being female and the remaining 14.3% being male. The Kaplan-Meier curves indicated that patients with pSPN who underwent primary tumor resection (PTR) and those who were younger than 70years old had significantly improved OS and CSS compared to those who did not undergo PTR or were aged 70years or older, respectively (P < 0.001). Male patients diagnosed with pSPN exhibited poor OS compared to female pSPN patients (P = 0.015). The multivariate Cox regression analysis indicated that age (OS: HR = 1.055, 95% CI = 1.027-1.084, P < 0.001. CSS: HR = 1.054, 95% CI = 1.019-1.091, P = 0.002) and PTR (OS: HR = 6.074, 95% CI = 1.922-19.194, P = 0.002. CSS: HR = 4.912, 95% CI = 1.188-20.312, P = 0.028) were independent prognostic factors for both OS and CSS. Moreover, tumor size (≥ 5 vs < 5cm CSS: HR = 4.788, 95% CI = 1.012-22.661, P = 0.048) was an independent prognostic factor for CSS. The independent prognostic factors identified through the multivariate Cox regression analysis were utilized to construct a nomogram model for predicting both OS and CSS in patients with pSPN. The accuracy of the nomogram model was visually testified by the calibration plot with acceptable predictive performance. Although the majority of patients diagnosed with pSPN are females, it was observed that male patients tend to have poorer OS compared to their female counterparts. The independent prognostic factors identified in the study were age and PTR, which were associated with both OS and CSS. Tumor size was an independent prognostic factor for CSS. Patients who underwent PTR exhibited improved OS and CSS outcomes. The developed nomogram and corresponding reference table provided promising prognostic predictions for pSPN outcoms, serving as a valuable resource for clinicians and patients alike.

Predictors of trimodality therapy in patients with muscle-invasive bladder cancer and effect on survival.

Due to its unique advantages over radical cystectomy (RC), trimodality therapy (TMT) is increasingly being utilized by patients diagnosed with muscle-invasive bladder cancer (MIBC) who are not suitable for or refuse RC. However, achieving a satisfactory oncological outcome with TMT requires strict patient selection criteria, and the comparative oncological outcomes of TMT versus RC remain controversial. Patients diagnosed with non-metastatic MIBC who underwent TMT or RC were identified from the SEER database during 2004-2015. Before one-to-one propensity score matching (PSM), logistic regression was utilized to identify predictors of TMT. After matching, K-M curves were generated to estimate cancer-specific survival (CSS) and overall survival (OS) with log-rank to test the significance. Finally, we conducted univariate and multivariate Cox analyses to identify independent prognostic factors for CSS and OS. The RC and TMT groups included 5812 and 1260 patients, respectively, and the TMT patients were significantly older than the RC patients. Patients with advanced age, separated, divorced, or widowed (SDW) or unmarried marital status (married as reference), and larger tumor size (< 40mm as reference) were more likely to be treated with TMT. After PSM, TMT was found to be associated with worse CSS and OS, and it was identified as an independent risk factor for both CSS and OS. MIBC patients may not be carefully evaluated prior to TMT, and some non-ideal candidates underwent TMT. TMT resulted in worse CSS and OS in the contemporary era, but these results may be biased. Strict TMT candidate criteria and TMT treatment modality should be required.

Risk factors and survival prediction of young breast cancer patients with liver metastases: a population-based study.

The risk and prognosis of young breast cancer (YBC) with liver metastases (YBCLM) remain unclear. Thus, this study aimed to determine the risk and prognostic factors in these patients and construct predictive nomogram models. This population-based retrospective study was conducted using data of YBCLM patients from the Surveillance, Epidemiology, and End Results database between 2010 and 2019. Multivariate logistic and Cox regression analyses were used to identify independent risk and prognostic factors, which were used to construct the diagnostic and prognostic nomograms. The concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the performances of the established nomogram models. Propensity score matching (PSM) analysis was used to balance the baseline characteristics between the YBCLM patients and non-young patients with BCLM when comparing overall survival (OS) and cancer-specific survival (CSS). A total of 18,275 YBC were identified, of whom 400 had LM. T stage, N stage, molecular subtypes, and bone, lung, and brain metastases were independent risk factors for LM developing in YBC. The established diagnostic nomogram showed that bone metastases contributed the most risk of LM developing, with a C-index of 0.895 (95% confidence interval 0.877-0.913) for this nomogram model. YBCLM had better survival than non-young patients with BCLM in unmatched and matched cohorts after propensity score matching analysis. The multivariate Cox analysis demonstrated that molecular subtypes, surgery and bone, lung, and brain metastases were independently associated with OS and CSS, chemotherapy was an independent prognostic factor for OS, and marital status and T stage were independent prognostic factors for CSS. The C-indices for the OS- and CSS-specific nomograms were 0.728 (0.69-0.766) and 0.74 (0.696-0.778), respectively. The ROC analysis indicated that these models had excellent discriminatory power. The calibration curve also showed that the observed results were consistent with the predicted results. DCA showed that the developed nomogram models would be effective in clinical practice. The present study determined the risk and prognostic factors of YBCLM and further developed nomograms that can be used to effectively identify high-risk patients and predict survival outcomes.

A nomogram for predicting cancer-specific survival in patients with uterine clear cell carcinoma: a population-based study

Uterine clear cell carcinoma (UCCC) is a relatively rare endometrial cancer. There is limited information on its prognosis. This study aimed to develop a predictive model predicting the cancer-specific survival (CSS) of UCCC patients based on data from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018. A total of 2329 patients initially diagnosed with UCCC were included in this study. Patients were randomized into training and validation cohorts (7:3). Multivariate Cox regression analysis identified that age, tumor size, SEER stage, surgery, number of lymph nodes detected, lymph node metastasis, radiotherapy and chemotherapy were independent prognostic factors for CSS. Based on these factors, a nomogram for predicting the prognosis of UCCC patients was constructed. The nomogram was validated using concordance index (C-index), calibration curves, and decision curve analyses (DCA). The C-index of the nomograms in the training and validation sets are 0.778 and 0.765, respectively. Calibration curves showed good consistency of CSS between actual observations and nomogram predictions, and DCA showed that the nomogram has great clinical utility. In conclusion, a prognostic nomogram was firstly established for predicting the CSS of UCCC patients, which can help clinicians make personalized prognostic predictions and provide accurate treatment recommendations.

PIK3CA Mutations as a Prognostic Factor in Patients With Residual Rectal Cancer After Neoadjuvant Chemoradiotherapy.

PIK3CA mediates various cellular processes, such as transformation, tumor initiation and proliferation, and resistance to apoptosis. This study was conducted to identify the clinical significance and prognostic effect of PIK3CA mutations in patients with residual rectal cancer who underwent surgery after neoadjuvant chemoradiotherapy (NACRT). Formalin-fixed and paraffin-embedded surgical specimens were collected from 128 patients between January 2006 and December 2011 and analyzed using real-time polymerase chain reaction for hotspot mutations in exons 9 and 20 of the PIK3CA gene. Of the 128 patients, 109 were analyzed and 19 were excluded because of poor DNA quality. Mutations in PIK3CA were identified in three patients (2.8%), all of which were detected in exon 20 of the PIK3CA gene. PIK3CA mutations significantly correlated with lymphatic invasion (p=0.016), lymph node metastasis (p=0.034), and higher pathological disease stage (p=0.040). By univariate analysis, patients with PIK3CA mutations were observed to have significantly shorter cancer-specific survival (CSS) (p=0.001) and disease-free survival (DFS) (p=0.006) than PIK3CA wild-type patients. However, PIK3CA mutations were not an independent prognostic factor for CSS (p=0.319) or DFS (p=0.219) in multivariate modeling. Our findings indicate that PIK3CA mutation plays a role in oncogenesis in rectal cancer and may be considered as a candidate therapeutic approach targeting the PIK3/Akt/mTOR pathway in patients with residual rectal cancer after NACRT.