Construction of a new tool for predicting cancer-specific survival in papillary thyroid cancer patients who have not received surgery.

Background: The prevalence of papillary thyroid cancer is gradually increasing and the trend of youthfulness is obvious. Some patients may not be able to undergo surgery, which is the mainstay of treatment, due to physical or financial reasons. Therefore, the prediction of cancer-specific survival (CSS) in patients with non-operated papillary thyroid cancer is necessary. Methods: Patients' demographic and clinical information was extracted from the Surveillance, Epidemiology, and End Results database. SPSS software was used to perform Cox regression analyses as well as propensity score matching analyses. R software was used to construct and validate the nomogram. X-tile software was used to select the best cutoff point for patient risk stratification. Results: A total of 1319 patients were included in this retrospective study. After Cox regression analysis, age, grade, T stage, M stage, radiotherapy, and chemotherapy were used to construct the nomogram. C-index, calibration curves, and receiver operating characteristic curves all verified the high predictive accuracy of the nomogram. The decision curve analysis demonstrated that patients could gain clinical benefit from this predictive model. Survival curve analysis after propensity score matching demonstrated the positive effects of radiotherapy on CSS in non-operated patients. Conclusion: Our retrospective study successfully established a nomogram that accurately predicts CSS in patients with non-operated papillary thyroid cancer and demonstrated that radiotherapy for operated patients can still help improve prognosis. These findings can help clinicians make better choices.

Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value. The Shapley Additive Explanations (SHAP) method was employed to investigate the key factors influencing the prediction process. Survival analysis methods were used to compare the survival rates of different treatment options. The CatBoost model yielded the best results (AUC = 0.939, sensitivity = 0.877, accuracy = 0.877). SHAP interpreters revealed that the T stage, cancer stage, age, cores positive percentage, prostate-specific antigen, and Gleason score were the most critical factors in predicting treatment options. The study found that surgery significantly improved survival rates, with patients undergoing surgery experiencing a 20.36% increase in 10-year survival rates compared with those receiving non-surgical treatments. Among surgical options, radical prostatectomy had the highest 10-year survival rate at 89.2%. This study successfully developed a predictive model to guide treatment decisions for prostate cancer. Moreover, the model enhanced the transparency of the decision-making process, providing clinicians with a reference for formulating personalized treatment plans.

Trends in the use of granulocyte colony stimulating factors for older patients with cancer, 2010 to 2019.

INTRODUCTION: Older patients with cancer receiving myelosuppressive treatment are at an increased risk for developing febrile neutropenia (FN) or having chemotherapy dose-reductions or delays, resulting in suboptimal health outcomes. Granulocyte colony stimulating factors (G-CSF) are effective medications to reduce these adverse events and are recommended for patients ≥65 years receiving chemotherapy with >10 % FN risk. We sought to characterize the trends and predictors of G-CSF use between the youngest-old (66-74 years), middle-old (75-84 years), and oldest-old (≥85 years) patients with cancer. MATERIALS AND METHODS: We used registry data from SEER-Medicare for breast, lung, ovarian, colorectal, esophageal, gastric, uterine, prostate, pancreatic cancer, and non-Hodgkin lymphoma (NHL) diagnoses from 2010 to 2019. Cox proportional hazard analysis was used. RESULTS: Overall, 41.4 % of patients received G-CSF from chemotherapy initiation to three days after completion of the first chemotherapy course. The use rate remained relatively stable for all cancers, except for an increase in use for those with pancreatic cancer. G-CSF use decreased as patients got older. The oldest-old were 43.0 % (95 % confidence interval: 40.7-45.2 %) less likely to receive G-CSF compared to the youngest-old. Patients with breast cancer or NHL were more likely to receive G-CSF than those with other cancers. Patients who were female, married, White or Hispanic, and had fewer comorbidities were more likely to receive G-CSF. DISCUSSION: G-CSF is used less often in populations at higher risk of developing FN and related complications. Improving adherence to recommendations can improve health outcomes, especially in the oldest adults, older males, and Black patients.

Prognosis and treatment regimens for patients with different lymph node statuses in locally advanced cervical cancer.

OBJECTIVE: The survival outcomes of Stage IIIC1 in FIGO 2018 showed significant heterogeneity and it seems unreasonable to administer a uniform treatment regimen for Stage IIIC1 patients. This study aimed to assess the survival outcomes among patients with locally advanced cervical cancer based on various lymph node statuses, T-stage classifications, and treatment modalities. METHODS: This is a population-based cohort study utilizing the Surveillance, Epidemiology, and End Results Program from 2004 to 2018. Propensity score-based inverse probability of treatment weighting was used to achieve covariate balance. Women with locally advanced cervical cancer on different lymph node statuses who underwent radical hysterectomy + pelvic lymphadenectomy + chemoradiotherapy, chemoradiotherapy, or radiotherapy alone were examined. Trends, patient characteristics, and survival outcomes were compared across different treatment regimens. RESULTS: Among 8777 patients analyzed, patients with early T-stage and married were identified as independent protective factors for cancer-specific survival regardless of lymph node status. The survival outcomes ranked in descending order as follows: T1N0>T2N0>T1N1 = T2N1>T3N0>T3N1. Therefore, the FIGO Stage IIIC1 was re-stratified into IIC (T1N1+T2N1) and IIIC1(T3N1). Patients who underwent radical hysterectomy combined with adjuvant therapy exhibited superior 5-year cancer-specific survival rates compared to those treated with chemoradiotherapy among IB3, IIA2, and IIC. The therapeutic efficacy of chemoradiotherapy surpassed that of radiotherapy alone in IIIA, IIIB, IIIC1(T3N1), and IVA patients. CONCLUSION: Restratification of Stage IIIC1 based on T-stage effectively discerns patients with divergent prognoses. Radical surgery + chemoradiotherapy is significantly associated with improved survival in early T-stage, regardless of lymph node status in locally advanced cervical cancer.

Comparison of prognosis between oncocytic thyroid carcinoma and follicular thyroid carcinoma: a population-based propensity score matching analysis.

BACKGROUND: Oncocytic thyroid carcinoma (OTC) is a rare subtype of thyroid cancer known for its distinctive morphology and high likelihood of recurrence, setting it apart from follicular thyroid carcinoma (FTC). Despite this, there is limited research comparing the clinicopathological characteristics and outcomes of OTC and FTC. METHODS: We retrospectively searched through the Surveillance, Epidemiology, and End-Results (SEER) database (2004-2015) for histologically diagnosed OTC and FTC patients. Kaplan-Meier analysis, propensity score matching (PSM), univariate Cox proportional risk regression model, and subgroup analysis were employed to investigate the prognostic effect of clinicopathological features and treatment regimens on survival outcomes of OTC and FTC patients. RESULTS: 2329 OTC patients and 5679 FTC patients were included in the study. OTC patients were prone to older age, white race, lymph node metastasis, distal metastasis, extension and multiple primary tumors compared with FTC patients. After using a 1:1 PSM matching ratio, there were no significant differences in demographic and clinicopathological characteristics between the matched groups. Further Cox regression analysis showed that OTC patients had lower overall survival (OS) and cancer-specific survival (CSS) in contrast with FTC patients. Subgroup survival analysis suggested that the OTC patients were related to lower OS in subgroups including those over 55 years old, male sex, white ethnicity, extrathyroidal extension, single primary tumor, surgery and without chemotherapy compared with the FTC patients in these subgroups. In addition, the OTC patients were connected with lower CSS in subgroups including male sex, white ethnicity, married status, tumor size is less than 20 mm or more than 40 mm, N0 stage, localized stage, single primary tumor, surgery, radiotherapy, and without chemotherapy compared with the FTC patients in these subgroups. Meanwhile, the OTC patients had lower CSS compared to FTC patients regardless of age and extrathyroidal extension. CONCLUSIONS: The results suggested that OTC patients have unique clinical features and poorer prognoses compared to FTC patients. Surgical resection and radioactive iodine therapy are recommended for OTC patients and FTC patients. It is worth noting that the prognosis of OTC relies largely on the selection of treatment strategies. Therefore, our results highlighted the clinical significance of the early distinguishment and the correct choice of treatment in OTC patients.

Adult Hodgkin lymphoma incidence trends in the United States from 2000 to 2020.

Hodgkin lymphoma (HL) is a rare malignancy affecting the lymphatic system. Our study examined the incidence rates of adult HL based on sex, race/ethnicity, age, and histological subgroups in the United States (US) from 2000 to 2020. Data for this study were extracted from the Surveillance, Epidemiology, and End Results 22 database. HL patients were identified utilizing the International Classification of Diseases for Oncology version 3 and categorized as classical HL, lymphocyte-rich/mixed cell/lymphocyte depleted, nodular sclerosis, classical HL, not otherwise specified, and nodular lymphocyte-predominant HL. The study reported average annual percent change (AAPC). All estimates were presented as counts and age-standardized incidence rates (ASIRs) per 100,000 individuals. Between 2000 and 2019, a total of 70,924 cases of HL were reported in the US. Classical HL was the predominant subtype (94.27%), and most incident cases were among non-Hispanic Whites (66.92%) and those aged 20-29 years (24.86%). The ASIR per 100,000 population was 3.83 for men and 2.92 for women. Both sexes showed declines in the AAPCs between 2000 and 2019 (- 0.64% [- 0.99, - 0.28] and - 0.40% [- 0.77, - 0.03] for men and women, respectively). There was a significant decrease in ASIRs after COVID-19 among both sexes (percent change: - 7.49% [- 11.58, - 3.40]). Throughout all age groups, men had a higher incidence rate compared to women, except for those aged 20-29 years. Although the overall HL incidence rate was lowered in the study period from 2000 to 2019, a dramatic decrease in ASIRs of HL patients following COVID-19 pandemic was observed.

Nomograms to predict lung metastasis in malignant primary osseous spinal neoplasms and cancer-specific survival in lung metastasis subgroup.

Purpose: To construct and validate nomograms for predicting lung metastasis probability in patients with malignant primary osseous spinal neoplasms (MPOSN) at initial diagnosis and predicting cancer-specific survival (CSS) in the lung metastasis subgroup. Methods: A total of 1,298 patients with spinal primary osteosarcoma, chondrosarcoma, Ewing sarcoma, and chordoma were retrospectively collected. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic analysis were used to identify the predictors for lung metastasis. LASSO and multivariate Cox analysis were used to identify the prognostic factors for 3- and 5-year CSS in the lung metastasis subgroup. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA) were used to estimate the accuracy and net benefits of nomograms. Results: Histologic type, grade, lymph node involvement, tumor size, tumor extension, and other site metastasis were identified as predictors for lung metastasis. The area under the curve (AUC) for the training and validating cohorts were 0.825 and 0.827, respectively. Age, histologic type, surgery at primary site, and grade were identified as the prognostic factors for the CSS. The AUC for the 3- and 5-year CSS were 0.790 and 0.740, respectively. Calibration curves revealed good agreements, and the Hosmer and Lemeshow test identified the models to be well fitted. DCA curves demonstrated that nomograms were clinically useful. Conclusion: The nomograms constructed and validated by us could provide clinicians with a rapid and user-friendly tool to predict lung metastasis probability in patients with MPOSN at initial diagnosis and make a personalized CSS evaluation for the lung metastasis subgroup.

Prognostic Nomogram, Demographics and Comparative Analysis of Urinary Bladder Small Cell and Large Cell Neuroendocrine Carcinoma.

BACKGROUND: This retrospective study aims to provide a comprehensive analysis of the demographics, survival rates, and therapeutic approaches of small-cell neuroendocrine carcinoma (SCNEC) and large-cell neuroendocrine carcinoma (LCNEC) while highlighting key differences compared to common urinary bladder cancers. METHODS: Our analysis utilized the Surveillance, Epidemiology, and End Results database (SEER), and data was collected from 2000-2020. RESULTS: A total of 1040 cases of urinary bladder SCNEC and LCNEC were identified. Most patients were over the age of 80 years (33.2%), male (78.9%), and Caucasian (83.6%). Most tumors were over 4.1cm (47.4%) and in the lateral wall of the bladder (37.8%). The overall 5-year survival was 22.1% (95% confidence interval (95% CI):20.7-23.5). The 5-year survival by sex was greatest for the female population (28.0%; (95% CI: 24.5-35.0). For treatment modality, the 5-year survival for each was as follows: surgery, 12.5% (95% CI: 10.5-14.5) multimodality therapy (surgery and chemotherapy), 31.1% (95% CI: 28.5-33.7) and combination (surgery, chemotherapy, and radiation) 32.8% (95% CI: 29.1-36.5). On multivariable analysis, positive nodal status hazar ratio (HR)(HR3.65 [95% CI: 2.34-5.71], P < .001) was identified as a negative predictor for survival, and increasing age was nearly significant for a worse prognosis (P = .052). The prognostic nomogram that was created to predict patient survivability mirrored the findings from the statistical analysis, with a statistically significant difference found in race, treatment modality, and tumor stage. CONCLUSIONS: SCNEC and LCNEC are rare yet highly intrusive subtypes of bladder cancer that usually affect Caucasian males over the age of 80 years old. The study identifies older age and positive nodal status as adverse prognostic indicators. Our findings offer crucial insights that can inform future clinical guidelines and serve as a basis for more tailored treatment strategies for these aggressive subtypes of bladder cancer.

Tumor deposits should not be placed in the M category of TNM: A comparative survival analysis using SEER data.

Tumor deposits (TD) are tumor nodules in the lymphatic drainage area of colorectal cancer patients, and they are currently classified in the N category in the TNM classification. However, due to the associated poor prognosis, some small cohort studies suggest that TD belong in the M category. A retrospective study using The Surveillance, Epidemiology, and End Results program (SEER) data was performed in Stages III and IV colon carcinoma (CC) patients to evaluate the prognostic impact of TD. In multivariate analysis, TD have significantly negative effect on survival in both stages (Stage III HR = 1.4 [95% CI 1.4-1.5] and Stage IV HR = 1.3 [95% CI 1.2-1.3]). In Stage III, 5-year overall survival (OS) for patients with TD 49%, whereas it was 64% for patients without TD (p < .001). Additionally, in Stage IV patients without TD, the 5-year OS rates are superior at 21% compared to patients with TD, who show 5-year OS rate of 10% (p < .001). Stage III patients with TD (5-year OS 49%) have a significantly better prognosis compared to Stage IV patients (5-year OS 17%, p < .001). Therefore, despite the previous suggestions, this large scale study (n = 52,332) on outcomes in CC does not support the classification of TD in Stage IV.

Is postoperative adjuvant radiotherapy necessary for patients with esophageal cancer after neoadjuvant chemoradiotherapy? An analysis based on the SEER database.

OBJECTIVES: To evaluate the outcomes of adjuvant radiotherapy in patients with esophageal cancer (EC) who underwent esophagectomy following neoadjuvant chemoradiotherapy (NCRT). METHODS: The data of EC patients who received adjuvant therapy after NCRT between 2004 to 2019 was retrieved from the SEER database. The patients were split into the adjuvant radiotherapy with or without chemotherapy (RT±CT) and the adjuvant chemotherapy (CT) groups. The process of propensity score matching (PSM) was employed. RESULTS: Following PSM, 157 patients in total were recruited in each treatment group. There were no significant variations in either overall survival (OS) or cancer-specific survival (CSS) between the RT±CT and CT groups (median OS: 28 months versus. 51 months, p=0.063; median CSS: 31 months versus. 52 months, p=0.16). Within the CT group, patients with ypI/II or cI/II tumor stage, positive lymph node ratio (LNR) ≤0.1, and tumor size ≥50 mm (p<0.05) had higher OS compared to the RT±CT groups. Among patients with cT3-4 tumors in N-stage downstaging group, the OS and CSS were significantly greater for those underwent RT±CT as opposed to the CT group (5-year OS:56.6% versus 19.4%, p=0.042; 5-year CSS:67.9% versus. 19.4%, p=0.023). Multivariate Cox regression analysis identified the tumor histology grade as an independent prognostic factor of OS and CSS. CONCLUSION: Radiotherapy-based adjuvant therapy does not significantly improve the prognosis of EC patients after NCRT, although it may provide a survival benefit for patients with cT3-4 tumors in N-stage downstaging.

Prognostic Nomograms for Patients With NF-Pan-NET After Pancreatectomy: A Retrospective Analysis Based on SEER Database.

AIMS: Surgical resection is the primary treatment option for patients diagnosed with nonfunctional pancreatic neuroendocrine tumors (NF-Pan-NETs). However, the postoperative prognostic evaluation for NF-Pan-NET patients remains obscure. This study aimed to construct an efficient model to predict the prognosis of NF-Pan-NET patients who have received surgical resection. METHODS: NF-Pan-NET patients after pancreatectomy were retrieved from the SEER database for the period of 2010 to 2019. A total of 2844 patients with NF-Pan-NET from SEER database were included in our study. After careful screening, six clinicopathological variables including age, grade, AJCC T stage, AJCC N stage, AJCC M stage, and chemotherapy were selected to develop nomograms to predict overall survival (OS) and cancer-specific survival (CSS) respectively of the patients. RESULTS: The novel models demonstrated high accuracy and discrimination in prognosticating resected NF-Pan-NET through various validation methods. Furthermore, the risk subgroups classified by the newly developed risk stratification systems based on the nomograms exhibited significant differences in both OS and CSS, surpassing the efficacy of the AJCC 8th TNM staging system. Novel nomograms and corresponding risk classification systems were developed to predict OS and CSS in patients with NF-Pan-NET after pancreatectomy. CONCLUSION: The models demonstrated superior performance compared to traditional staging systems, providing clinicians with more accurate and personalized guidance for postoperative surveillance and treatment.

Disparities in pediatric parotid cancer treatment and presentation: A National study.

OBJECTIVES: Although parotid gland malignancies are uncommon, they nevertheless represent a cause of morbidity and mortality in the pediatric population. Few studies have sought to identify disparities related to their presentation, treatment, and survival. There is a need to understand these variations to improve care for historically underrepresented groups. STUDY DESIGN: Retrospective Cohort Study. SETTING: Surveillance, Epidemiology, and End Results (SEER) Program Database. METHODS: Analysis of pediatric patients with parotid gland malignancies between 2000 and 2019. Race and ethnicity were classified as Non-Hispanic White, Non-Hispanic Black, Asian, and Hispanic for multivariable analysis. Outcomes included tumor size and stage at diagnosis, survival, and need for facial nerve sacrifice. Kaplan-Meier analysis was used to analyze survival. Multivariable logistic regression was conducted to identify predictors of outcomes. RESULTS: 149 patients met the criteria for inclusion. Stratified by race/ethnicity, Non-Hispanic Black (Median 23 mm, IQR 15-33), Asian (30 mm, 14-32), and Hispanic (23 mm, 20-28) patients had larger tumors at presentation than Non-Hispanic White patients (18 mm, 12-25, p = 0.017). Disease-specific survival differed by time-to-treatment (log-rank, p = 0.01) and overall survival differed by income (p < 0.001). On multivariable analysis, Hispanic patients were more likely to experience facial nerve sacrifice (OR 3.71, 95%CI 1.25-11.6, p = 0.020), and Non-Hispanic Black (OR 3.37, 0.95-11.6, = 0.053) and Asian (OR 5.67, 1.46-22.2, p = 0.011) patients presented with larger tumors compared to Non-Hispanic White patients. CONCLUSIONS: Variations in presentation and treatment exist across race and ethnicity in pediatric parotid cancer. Identifying these disparities may help improve access and outcomes for underserved patient populations. LEVEL OF EVIDENCE: III.

A novel nomogram based on the number of positive lymph nodes can predict the overall survival of patients with pancreatic head cancer after radical surgery.

BACKGROUND: This study aimed to construct a novel nomogram based on the number of positive lymph nodes to predict the overall survival of patients with pancreatic head cancer after radical surgery. MATERIALS AND METHODS: 2271 and 973 patients in the SEER Database were included in the development set and validation set, respectively. The primary clinical endpoint was OS (overall survival). Univariate and multivariate Cox regression analyses were used to screen independent risk factors of OS, and then independent risk factors were used to construct a novel nomogram. The C-index, calibration curves, and decision analysis curves were used to evaluate the predictive power of the nomogram in the development and validation sets. RESULTS: After multivariate Cox regression analysis, the independent risk factors for OS included age, tumor extent, chemotherapy, tumor size, LN (lymph nodes) examined, and LN positive. A nomogram was constructed by using independent risk factors for OS. The C-index of the nomogram for OS was 0.652 [(95% confidence interval (CI): 0.639-0.666)] and 0.661 (95%CI: 0.641-0.680) in the development and validation sets, respectively. The calibration curves and decision analysis curves proved that the nomogram had good predictive ability. CONCLUSIONS: The nomogram based on the number of positive LN can effectively predict the overall survival of patients with pancreatic head cancer after surgery.

A prognostic nomogram for patients with HR+ mucinous breast carcinoma based on the SEER database and a Chinese cohort study.

Purpose: The study aimed to develop a nomogram model for individual prognosis prediction in patients with hormone receptors positive (HR+) mucinous breast carcinoma (MBC) and assess the value of neoadjuvant chemotherapy (NAC) in this context. Methods: A total of 6,850 HR+ MBC patients from the SEER database were identified and randomly (in a 7:3 ratio) divided into training cohorts and internal validation cohorts. 77 patients were enrolled from the Chongqing University Cancer Hospital as the external validation cohort. Independent risk factors affecting overall survival (OS) were selected using univariate and multivariate Cox regression analysis, and nomogram models were constructed and validated. A propensity score matching (PSM) approach was used in the exploration of the value of NAC versus adjuvant chemocherapy (AC) for long-term prognosis in HR+ MBC patients. Results: Multivariate Cox regression analysis showed 8 independent prognostic factors: age, race, marital status, tumor size, distant metastasis, surgery, radiotherapy, and chemotherapy. The constructed nomogram model based on these 8 factors exhibited good consistency and accuracy. In the training group, internal validation group and external validation group, the high-risk groups demonstrated worse OS (p<0.0001). Subgroup analysis revealed that NAC had no impact on OS (p = 0.18), or cancer specific survival (CSS) (p = 0.26) compared with AC after PSM. Conclusions: The established nomogram model provides an accurate prognostic prediction for HR+ MBC patients. NAC does not confer long-term survival benefits compared to AC. These findings provide a novel approach for prognostic prediction and clinical practice.

Association between tumor size and prognosis in patients with small bowel adenocarcinoma-a SEER-based study.

Background: The association between small-bowel adenocarcinoma (SBA) tumor size and prognosis is unclear, and we used the Surveillance, Epidemiology, and End Results (SEER) database to assess the prognostic value of SBA tumor size. Methods: Patients with postoperative SBA were selected from the SEER database, and overall survival (OS) and cancer-specific survival (CSS) were used as outcome variables. Tumor size was used as a categorical and continuous variable, respectively, to adjust for confounders and analyze the association between SBA tumor size and prognosis using Cox proportional hazard regression, and the results were visualized using restricted cubic splines (RCS). Spearman correlation coefficient was used to evaluate the statistical correlation between tumor size and tumor invasion depth (T-stage). Kaplan-Meier survival curves were used to estimate OS at different T stages. Results: When the tumor size was analyzed as a quantitative variable, the adjusted covariate model showed that the HR was 1.008 (P = 0.04) for OS and 1.021 (P = 0.03) for CSS. And regardless of OS or CSS, when the tumor size < 3-4 cm, there was a close linear relationship between tumor size and HR. What's more, in the SEER database, the 5-year survival rates of T1, T2, T3 and T4 patients were 81.8 %, 81.1 %, 66.0 % and 50.9 % (P < 0.001) according to AJCC T-stage. However, in the modified T-stage (mT), these rates were 82.8 %, 70.6 %, 60.7 % and 39.8 % (P < 0.001). When patients within each of the AJCC T stages were stratified by mT stages, significant survival heterogeneity was observed within each of the AJCC T1 to T4 stages(P < 0.001). Conclusion: When tumor size is used in a quantitative way, tumor size is an independent predictor of poor outcome in patients with SBA. Furthermore, we established a modified T-stage based on tumor size and depth of invasion.

Prognostic nomogram of overall survival for radiation therapy in hepatocellular carcinoma: a population study based on the SEER database and an external cohort.

Purpose: Radiotherapy (RT) plays an important role in the treatment of hepatocellular carcinoma (HCC). To screen patients who benefit most from RT, a nomogram for survival prediction of RT based on a large sample of patients with HCC was created and validated. Methods: A total of 2,252 cases collected from the Surveillance, Epidemiology, and End Results (SEER) database were separated into a training or an internal validation cohort in a 7:3 ratio (n = 1,565:650). An external validation cohort of cases from our institute was obtained (n = 403). LASSO regression and Cox analyses were adopted to develop a nomogram for survival prediction. The decision curve analysis (DCA), calibration curve, and time-dependent receiver operating characteristic curves (TROCs) demonstrated the reliability of the predictive model. Results: For patients with HCC who received RT, the analyses revealed that the independent survival prediction factors were T stage {T2 vs. T1, hazard ratio (HR) =1.452 [95% CI, 1.195-1.765], p < 0.001; T3 vs. T1, HR = 1.469 [95% CI, 1.168-1.846], p < 0.001; T4 vs. T1, HR = 1.291 [95% CI, 0.951-1.754], p = 0.101}, N stage (HR = 1.555 [95% CI, 1.338-1.805], p < 0.001), M stage (HR = 3.007 [95% CI, 2.645-3.418], p < 0.001), max tumor size (>2 and ≤5 vs. ≤2 cm, HR = 1.273 [95% CI, 0.992-1.633], p = 0.057; >5 and ≤10 vs. ≤2 cm, HR = 1.625 [95% CI, 1.246-2.118], p < 0.001; >10 vs. ≤2 cm, HR = 1.784 [95% CI, 1.335-2.385], p < 0.001), major vascular invasion (MVI) (HR = 1.454 [95% CI, 1.028-2.057], p = 0.034), alpha fetoprotein (AFP) (HR = 1.573 [95% CI, 1.315-1.882], p < 0.001), and chemotherapy (HR = 0.511 [95% CI, 0.454-0.576], p < 0.001). A nomogram constructed with these prognostic factors demonstrated outstanding predictive accuracy. The area under the curve (AUC) in the training cohort for predicting overall survival (OS) at 6, 12, 18, and 24 months was 0.824 (95% CI, 0.803-0.846), 0.824 (95% CI, 0.802-0.845), 0.816 (95% CI, 0.792-0.840), and 0.820 (95% CI, 0.794-0.846), respectively. The AUCs were similar in the other two cohorts. The DCA and calibration curve demonstrated the reliability of the predictive model. Conclusion: For patients who have been treated with RT, a nomogram constructed with T stage, N stage, M stage, tumor size, MVI, AFP, and chemotherapy has good survival prediction ability.

Prognostic factors and overall survival in pelvic Ewing's sarcoma and chordoma: A comparative SEER database analysis.

Background: This study aimed to develop and validate nomograms to predict overall survival (OS) for pelvic Ewing's sarcoma (EWS) and chordoma, identify prognostic factors, and compare outcomes between the two conditions. Methods: We identified patients diagnosed with pelvic EWS or chordoma from the SEER database (2001-2019). Independent risk factors were identified using univariate and multivariate Cox regression analyses, and these factors were used to construct nomograms predicting 3-, 5-, and 10-year OS. Validation methods included AUC, calibration plots, C-index, and decision curve analysis (DCA). Kaplan-Meier curves and log-rank tests compared survival differences between low- and high-risk groups. Results: The study included 1175 patients (EWS: 611, chordoma: 564). Both groups were randomly divided into training (70 %) and validation (30 %) cohorts. OS was significantly higher for chordoma. Multivariate analysis showed year of diagnosis, income, stage, and surgery were significant for EWS survival, while age, time to treatment, stage, and surgery were significant for chordoma survival. Validation showed the nomograms had strong predictive performance and clinical utility. Conclusions: The nomograms reliably predict overall survival (OS) in pelvic EWS and chordoma, helping to identify high-risk patients early and guide preventive measures. The study also found that survival rates are significantly higher for chordoma, highlighting different prognostic profiles between EWS and chordoma.

Development and validation of a nomogram to predict cancer-specific survival of patients with large hepatocellular carcinoma accepting surgical resection: a real-world analysis based on the SEER database.

Background: Only a small percentage of patients with large hepatocellular carcinoma (HCC) can undergo surgical resection (SR) therapy while the prognosis of patients with large HCC is poor. However, innovations in surgical techniques have expanded the scope of surgical interventions accessible to patients with large HCC. Currently, most of the existing nomograms are focused on patients with large HCC, and research on patients who undergo surgery is limited. This study aimed to establish a nomogram to predict cancer-specific survival (CSS) in patients with large HCC who will undergo SR. Methods: The study retrieved data from the Surveillance, Epidemiology, and End Results (SEER) database encompassing patients with HCC between 2010 and 2015. Patients with large HCC accepting SR were eligible participants. Patients were randomly divided into the training (70%) and internal validation (30%) groups. Patients from Air Force Medical Center between 2012 and 2019 who met the inclusion and exclusion criteria were used as external datasets. Demographic information such as sex, age, race, etc. and clinical characteristics such as chemotherapy, histological grade, fibrosis score, etc. were analyzed. CSS was the primary endpoint. All-subset regression and Cox regression were used to determine the relevant variables required for constructing the nomogram. Decision curve analysis (DCA) was used to evaluate the clinical utility of the nomogram. The area under the receiver operating characteristic curve (AUC) and calibration curve were used to validate the nomogram. The Kaplan-Meier curve was used to assess the CSS of patients with HCC in different risk groups. Results: In total, 1,209 eligible patients from SEER database and 21 eligible patients from Air Force Medical Center were included. Most patients were male and accepted surgery to lymph node. The independent prognostic factors included sex, histological grade, T stage, chemotherapy, α-fetoprotein (AFP) level, and vascular invasion. The CSS rate for training cohort at 12, 24, and 36 months were 0.726, 0.731, and 0.725 respectively. The CSS rate for internal validation cohort at 12, 24, and 36 months were 0.785, 0.752, and 0.734 respectively. The CSS rate for external validation cohort at 12, 24, and 36 months were 0.937, 0.929, and 0.913 respectively. The calibration curve demonstrated good consistency between the newly established nomogram and real-world observations. The Kaplan-Meier curve showed significantly unfavorable CSS in the high-risk group (P<0.001). DCA demonstrated favorable clinical applicability of the nomogram. Conclusions: The nomogram constructed based on sex, histological grade, T stage, chemotherapy and AFP levels can predict the CSS in patients with large HCC accepting SR, which may aid in clinical decision-making and treatment.