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Background: Radioactive iodine (RAI) ablation therapy is a common minimally invasive treatment for patients diagnosed with differentiated thyroid cancer (DTC). Although previous studies have identified a link between RAI and the mortality from secondary solid cancers, the connection between RAI and leukemia remains under-researched. This study investigated the differential risk of leukemia and its subtypes in DTC patients following RAI treatment. Methods: DTC patients from the Surveillance, Epidemiology, and End Results (SEER) Registry 17 (2000-2019) were analyzed. The standard incidence ratio (SIR) and excess risk (ER) compared to the reference population were calculated. Results: Out of 196,569 DTC patients, 1381 patients developed various types of hematological malignancies. Leukemia was diagnosed in 508 of these patients, and it had the highest risk among the malignancies studied, with an SIR of 1.74 (95%CI: 1.59-1.9). The RAI group had an SIR of 2.12 (95%CI: 1.87-2.39), while the non-RAI group had an SIR was 1.45 (95%CI: 1.37-1.52) (p < 0.001). Those diagnosed before the age of 55 years had a conspicuously elevated risk (SIR 2.74) compared to those diagnosed at 55 years or older (SIR 1.53). American Indian/Alaska Native survivors manifested a pronounced leukemia risk with an SIR of 7.63 (95%CI: 2.46-17.8). Conclusions: RAI treatment increased the risk of developing leukemia when serving as adjuvant therapy in surgical patients (SIR 2.12). There exists a significant association between RAI treatment in DTC patients and the incidence of leukemia. This susceptibility seems to be modulated by factors including time since diagnosis, age, gender, and racial background.

Background: The impact of radiotherapy on the oncologic outcome of retroperitoneal liposarcoma (RPLS) remains controversial. The aim of this study was to evaluate the effect of radiotherapy on disease-specific survival (DSS) in a cohort of patients with RPLSs. Methods: In this population-based, retrospective cohort study, patients with localized RPLSs who underwent surgical therapy were identified from the Surveillance, Epidemiology, and End Results-17 cancer registry program. After propensity-score matching for potential confounders, multivariable logistic and Cox regression analyses were used to examine factors associated with DSS and radiotherapy. Results: From 2004 to 2020, 1692 patients with localized RPLS who underwent surgical therapy were identified (84.2% White, 44.6% female, mean age 62 years). Of those patients, 393 patients (23.2%) received perioperative radiotherapy. Patients who received radiotherapy had a higher rate of tumor size between 10 and 20 cm and unknown tumor grading. After propensity-score matching, multivariable adjusted Cox regression and Kaplan–Meier survival analysis demonstrated no improvement of DSS for patients who underwent radiotherapy (hazard ratio 1.04, confidence interval 0.81–1.32; log-rank p = 0.47). Patient age ≥80 years, larger tumor size, and tumor grading G3 versus G1/2 were associated with an increased risk of death due to RPLS. Subgroup analyses stratified by grading showed similar outcomes. Conclusions: The administration of perioperative radiotherapy did not improve DSS in patients undergoing surgery for localized RPLS in this population-based study. Therefore, the use of perioperative radiotherapy in these patients may be questioned. However, the findings should be interpreted with caution due to the inherent limitations of the Surveillance, Epidemiology, and End Results (SEER) database. [ABSTRACT FROM AUTHOR]

Background: Hepatic angiosarcoma (HA) is a rare malignant vascular neoplasm. Currently, there are no standardized protocols for treating HA. This study aims to understand clinicopathologic analysis, prognostic factors, and treatment outcomes comprehensively. Methods: The data retrieved from the SEER database was reviewed for hepatic angiosarcoma cases between 2000 and 2021. Results: A total of 389 patients with hepatic angiosarcoma were identified with a mean age of 63.9 years (SD ± 16). Most patients were male (64%), and per US census data, non-Hispanic Asians or Pacific Islanders were the most common race (17%). In known cases of tumor stage (61%), the most common tumor stage was distant (22%), and most were grade III (18%) tumors. Overall, the 3-year survival rate was 6.7% with a 95% confidence interval (95% CI 0.044–0.100), disease-specific survival at a 1-year survival rate was 4.43% (95% CI 0.023–0.083), and no patients survived by 3 years. The best overall survival rate was the 1-year rate for surgical resection, 18.20% (95% CI 0.075–0.441). Chemotherapy had a 1-year survival rate of 11% (95% CI 0.057–0.211), and radiation therapy had no survival significance (p = 0.2). Multivariate analysis shows age above 70 years (H.R. 1.67 (95% CI 1.181–2.381), p < 0.05), no surgical intervention (H.R. 2.29 (95% CI 1.585–3.336) p < 0.001), and distant stage (H.R. 2.54 (95% CI 1.696–3.805) p < 0.001) are negative prognostic factors, whereas female sex (H.R. 0.68 (95% CI 0.536–0.875) p < 0.05) is a positive prognostic factor. Conclusion: Increasing age (> 70 years), male sex, and distant stage were found to be strong predictors of poor survival outcomes. Patients had better outcomes when surgical resection and chemotherapy were included in their treatment. These results can provide continued evidence in the future management of patients with hepatic angiosarcoma. [ABSTRACT FROM AUTHOR]

Nomograms for predicting survival are well-established for colorectal adenocarcinoma but are less common for rectal mucinous adenocarcinoma (MAC). This study leverages Surveillance, Epidemiology, and End Results (SEER) database to develop a prognostic nomogram for rectal MAC, enhancing survival prediction and clinical decision-making. Data from the SEER (2004–2017) were analyzed, focusing on surgically treated rectal MAC patients. The study excluded cases with inadequate follow-up or incomplete data. Demographic and pathological variables, along with treatment modalities (radiotherapy and chemotherapy), were examined. A nomogram was developed to predict 1-, 3-, and 5-year cancer-specific survival (CSS), and its accuracy was validated using receiver operating characteristic (ROC) curves, calibration, and decision curve analysis (DCA). The study included 690 patients, segmented into training (483) and validation (207) cohorts. Significant factors affecting survival included age and cancer stage. The resulting nomogram, incorporating age and TNM stages, demonstrated a concordance index of 0.722 and was further validated through ROC analysis, calibration, and DCA, showing robust predictive performance and clinical utility. Age and TNM staging are critical predictors of CSS in rectal MAC patients post-surgery. The developed nomogram, utilizing these factors, offers improved prognostic accuracy and is a valuable tool for clinical practice, facilitating more informed treatment decisions. [ABSTRACT FROM AUTHOR]

Background: Research on mortality outcomes and non-cancer-related causes of death in patients with malignant brain tumors remains limited. This study aims to identify the prevalence of non-cancer-related causes of death after brain cancer (BC) diagnosis. Methods: Data of patients diagnosed with BC in the USA between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database were retrieved and analyzed. Standardized mortality ratios (SMRs) were calculated for all the reported causes of death. Results: A total of 59,663 deaths were reported during the follow-up period. The highest number of fatalities (34,677) occurred within the first year following BC diagnosis. BC-attributable deaths were the leading cause of mortality (55,482; 93%), followed by non-cancer deaths (3888; 6.5%). BC patients had an increased risk of non-cancer attributable deaths (SMR = 6.12; 95% CI 5.93–6.31) including heart diseases (N = 938; SMR = 5.3; 95% CI 4.96–5.65), cerebrovascular diseases (N = 453; SMR = 13.17; 95% CI 11.98–14.44), accidents and adverse effects (N = 227; SMR = 2.97; 95% CI 2.6–3.39), and septicemia (N = 155; SMR = 13.39; 95% CI 11.36–15.67). Conclusion: Compared to the general population, BC patients had a statistically significant higher risk of death from most of the reported causes. [ABSTRACT FROM AUTHOR]

Objective: In light of the incompletely defined metastatic patterns inherent to rhabdomyosarcoma (RMS), our objective was to analyze the clinicopathological attributes of various metastatic sites in patients afflicted with RMS. Additionally, we sought to identify population-level risk factors that contribute to metastasis in patients. Methods: Utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2000 to 2017, our study included a cohort of 1,300 patients diagnosed with RMS, each presenting with specific instances of metastasis. Statistical comparisons of categorical variables between groups were conducted using the chi-squared test or Fisher's exact test. Survival curves were constructed employing the Kaplan–Meier method and their comparative analysis was conducted using the log-rank test. Identification of the risk factors associated with site-specific metastasis in patients diagnosed with RMS was undertaken through the application of multivariate logistic regression analysis. Results: The observed incidence rates of metastasis to the lung, bone, liver, and brain among patients diagnosed with RMS were 13.1, 12.3, 2.5, and 1.2% respectively. The presence of lung, bone, liver, and brain metastases in patients with RMS was associated with a statistically significant reduction in cancer-specific survival. Factors indicative of increased risk for the development of lung metastasis in patients with RMS include male gender (in comparison to female), larger tumor volume, and tumor location in unfavorable sites (as compared to favorable sites). Risk factors for the occurrence of bone metastasis were male (as compared to female), larger tumor volume, and alveolar RMS (as compared to embryonal RMS). The median CSS for patients diagnosed with RMS and presenting with lung, bone, liver, and brain metastases were 15, 19, 5, and 8 months, respectively. Conclusion: Through an analysis of site-specific metastasis in patients diagnosed with RMS, we identified risk factors associated with lung and bone metastasis. These findings are of considerable significance for clinicians, are of considerable significance during the pre-treatment evaluation phase. The application of these findings has the potential to extend the survival duration of patients with RMS. [ABSTRACT FROM AUTHOR]

Purpose: Limited data are available on the impact of socioeconomic disparities on the survival of patients with non-muscle invasive urothelial carcinoma (NMIBC). Methods: We analyzed the Surveillance, Epidemiology, and End Results database to review the effects of sex, race, location, and socioeconomic factors on the survival of patients with NMIBC. We calculated 5-year overall survival (OS) and cancer-specific survival (CSS) using the log-rank test. The impact of socioeconomic factors on OS and CSS was analyzed using the Cox proportional hazards model adjusted for clinical characteristics. Hazard ratios (HR) and survival rates were reported with 95% confidence intervals (CI). Results: Analysis of 3831 patients showed that older age was associated with worse OS (HR 1.08 [1.08–1.09]) and CSS (HR 1.05 [1.04–1.06]). Women and men had similar OS (HR 0.91 [0.82–1.01]) and CSS (HR 1.12 [0.95–1.32]). Black patients had worse OS (HR 1.33 [1.08–1.62] and CSS [HR 1.54 [1.13–2.05]) than their White counterparts. Patients with an annual household income below $40,000 had worse outcomes compared to those with income above $70,000 for both OS (HR 1.79 [1.37–2.33]) and CSS (HR 1.924 [1.26–2.89]). Conclusions: There were no gender differences in survival outcomes of NMIBC. Older age, Black, American Indian/Alaskan Native, and patients with a household income below $40,000 appear to have worse survival. However, the area of residence did not seem to affect patient survival. [ABSTRACT FROM AUTHOR]

Background: High-grade colorectal neuroendocrine carcinoma (HCNEC) is a rare but aggressive subset of neuroendocrine tumors. This study was designed to construct a risk model based on comprehensive clinical and mutational genomics data to facilitate clinical decision making. Methods: A retrospective analysis was conducted using data from the Surveillance, Epidemiology, and End Results (SEER) database, spanning 2000 to 2019. The external validation cohort was sourced from two tertiary hospitals in Southwest China. Independent factors influencing both overall survival (OS) and cancer-specific survival (CSS) were identified using LASSO, Random Forest, and XGBoost regression techniques. Molecular data with the most common mutations in CNEC were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. Results: In this prognostic analysis, the data from 714 participants with HCNEC were evaluated. The median OS for the cohort was 10 months, whereas CSS was 11 months. Six variables (M stage, LODDS, Nodes positive, Surgery, Radiotherapy, and Chemotherapy) were screened as key prognostic indicators. The machine learning model showed reliable performance across multiple evaluation dimensions. The most common mutations of CNEC identified in the COSMIC database were TP53, KRAS, and APC. Conclusions: In this study, a refined machine learning predictive model was developed to assess the prognosis of HCNEC accurately and we briefly analyzed its genomic features, which might offer a valuable tool to address existing clinical challenges. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is a major contributor to cancer-related mortality, with liver metastases developing in approximately 25% of affected individuals. The presence of liver metastasis significantly deteriorates the prognosis for patients. The objective of this study is to predict liver metastasis in CRC patients by developing machine learning (ML)-based models, thereby aiding clinicians in the decision-making process for appropriate interventions. Methods: Retrospective analysis was performed using the Surveillance, Epidemiology, and End Results (SEER) database, and cases with CRC from 2010 to 2015 were extracted to the downstream analysis. Logistic regression (LR), Random Forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and LightGBM are applied to develop machine learning (ML) models to predict liver metastasis of CRC patient. To optimize the models, an improved weight-balancing algorithm was employed, enhancing the performance of the classifiers. The six models were tenfold cross-validated, and the optimal model was selected based on a combination of performance metrics. Shapley additive explanation (SHAP) was utilized to interpret the best-performing ML models globally, locally, and interactively. To ensure the model's reliability and generalizability, an external validation cohort of CRC cases from 2018 to 2021, obtained from a separate SEER database, was used for external evaluation. Results: In total, 50,062 patients with CRC were included in the analysis, with 5604 patients occurring liver metastasis. Among the six models evaluated, the CatBoost model showed excellent performance with the highest AUC of 0.8844. Moreover, the CatBoost model also outperformed the others in terms of recall (0.8060) and F1-score (0.6736). SHAP-based summary and force plots were used to interpret the CatBoost model. The interpretability analysis revealed that elevated carcinoembryonic antigen (CEA) levels, systemic therapy, N and T stages, and chemotherapy performed were the most significant indicators for predicting liver metastasis according to the optimal model. Furthermore, systemic therapy was suggested to increase liver metastasis risk in N0 stage patients, while it appeared to be beneficial in patients with lymph node metastasis. Preoperative radiation therapy was found to be more effective than postoperative radiation therapy. Validation using an external cohort of CRC cases from 2018 to 2021 further confirmed the robustness and stability of the CatBoost model, as its overall performance remained consistent with the internal validation results. Conclusion: Elevated levels of carcinoembryonic antigen (CEA) have been identified as a crucial clinical predictor for liver metastasis in CRC patients. Furthermore, the administration of systemic therapy to patients who do not exhibit lymph node involvement has been found to increase the risk of liver metastasis. In terms of radiation therapy, preoperative radiation appears to be more efficacious in controlling the risk of liver metastasis compared to postoperative radiation. This finding underscores the importance of optimizing treatment strategies based on the specific clinical context and patient characteristics. [ABSTRACT FROM AUTHOR]

Breast cancer is currently the most common malignant tumor affecting women's health worldwide. The rise in breast cancer metastases among patients is attributed to the inherent variability in metastatic behavior. In breast cancer, bones are the primary location for distant metastases, significantly impacting the survival rates of elderly (≥ 65) patients. The use of surgery and chemotherapy in this population is controversial. This study seeks to create a tool for forecasting overall survival (OS) in older breast cancer patients with bone metastases and to determine the optimal candidates for surgery and chemotherapy. Elderly female breast cancer patients with bone metastases from the Surveillance, Epidemiology, and End Results (SEER) database were included in this study and categorized into a training cohort and a validation cohort using R software. To identify independent predictors of OS in this population, both univariate and multivariate Cox regression analyses were conducted. Subsequently, a prognostic nomogram was created to estimate OS at 12, 24, and 36 months. The nomogram's accuracy and practical value were assessed using a calibration curve, area under the curve (AUC), and decision curve analysis (DCA). At the same time, a mortality risk classification system based on the nomogram was created to divide the population into high and low mortality risk categories, and subgroups were analyzed to determine the optimal candidates for surgery and chemotherapy. This study encompassed 2257 elderly female breast cancer patients with bone metastases, divided into 1581 participants for the training cohort and 676 for the validation cohort. Both univariate and multivariate Cox regression analyses validated those variables such as age, race, marital status, histological type, tumor grade, ER status, PR status, breast subtype, distant metastases (lung, liver, and brain), and treatment methods (surgery and chemotherapy) independently predicted OS in elderly female breast cancer patients with bone metastases (p < 0.05). Utilizing these independent predictors, a prognostic nomogram was developed to estimate OS at 12, 24, and 36 months. The calibration curves indicated that the nomogram's predictions closely matched the observed outcomes. The nomogram's AUC for forecasting OS at 12, 24, and 36 months was 0.753, 0.748, and 0.745 in the training cohort, and 0.744, 0.723, and 0.723 in the validation cohort. Additionally, the nomogram's AUC surpassed that of any individual independent predictor. DCA showed that the nomogram could achieve more net clinical benefit over a broader range of threshold probabilities. The nomogram-based risk classification system effectively sorted patients into two categories: low risk (≤ 820) and high risk (> 820). Subgroup analysis indicated that individuals classified as low-risk experienced the greatest advantage from surgery and chemotherapy (p < 0.05), whereas the high-risk group did not exhibit a statistically significant difference (p > 0.05). Drawing from the clinicopathological characteristics of elderly female breast cancer patients with bone metastases, this study developed a novel prognostic nomogram to forecast OS at 12, 24, and 36 months, enabling precise survival predictions. In addition, this study also constructed a mortality risk classification system, which can effectively help clinicians screen out the optimal candidates to benefit from surgery and chemotherapy and rationalize the allocation of medical resources. [ABSTRACT FROM AUTHOR]

BackgroundMethodsResultsConclusionsRetinoblastoma is the most common intraocular cancer in children, with significant variations in incidence and Survival. This study sought to evaluate nationwide retinoblastoma incidences and survival rates in the United States from 1996 to 2018.We extracted data from the North American Association of Central Cancer Registries (NACCR) and the National Program of Cancer Registries between 1996 and 2018. Cases were stratified by sex, age, race, Hispanic origin, urban or rural origin, stage of the disease, and state of residence and compared by laterality. We applied SEER*Stat version 8.4.0.1 software for age-adjusted incidence rates (AAIR) and annual average per cent change (AAPC) and JoinPoint version 4.9.1.0 software to assess incidence trends. Survival trends were evaluated with JPSurv online software.The study comprised 5730 patients with a crude incidence rate (CIR) of 0.89 per million. The incidence declined from 29.6 per million in the first year of life to 16.5 in the second year. The CIR for unilateral and bilateral diseases were 0.61 and 0.27, respectively. Males had a slightly higher and significant crude incidence of 0.93 versus 0.86 for females. Hispanics had the highest rate of 1.48 in general. Treatment data revealed chemotherapy usage in 39% of unilateral and 78% of bilateral patients. The 5-year cumulative relative Survival did not significantly differ between unilateral (96.8%) and bilateral (97.0%) patients. A slight but significant annual decline in CIR was observed, with a trend toward an increase in the percentage of patients diagnosed in the first year of life.This study indicated an overall decrease in incidence but a slight increase in early diagnosis. Findings underscore the need for consistent surveillance, early detection strategies, and personalized care to improve patient outcomes. The changes in the Survival in the unilateral disease require further investigations and mitigation strategies. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this research is to establish a prognostic nomogram for patients with distal cholangiocarcinoma (dCCA). Methods: We obtained clinical data from 2401 patients diagnosed with distal cholangiocarcinoma (dCCA) between 2010 and 2020 from the Surveillance, Epidemiology, and End Results database. These patients were randomly assigned to either the training or validation group in a ratio of 6:4. 228 patients were enrolled from 9 hospitals in China as the external validation cohort. Univariate and multifactorial Cox regression analyses were conducted to ascertain prognostic factors and prognostic nomograms were developed utilizing LASSO logistic regression analysis. We used the calibration curve, and area under the curve to validate the nomograms. Decision curve analysis was used to evaluate the model and its clinical applicability. Results: The findings demonstrated that Grade, M stages, Surgery, and Chemotherapy emerged as autonomous prognostic factors for the survival of individuals with dCCA. The developed nomograms exhibited satisfactory accuracy in forecasting 1-year, 3-year, and 5-year survival probabilities. Furthermore, the calibration curves indicated a strong concordance between the anticipated and observed outcomes. The AUC of the nomogram for 1-year, 3-year, 5 year overall survival (OS) predication were 0.809 (95%CI 78.5-83.3), 0.79 (95%CI 75.8-82.2) and 0.761 ((95%CI 72.3-80.0) in the training cohort, 0.79 (95%CI 75.9-82.0), 0.73 (95%CI 68.5-77.5), and 0.732(95%CI 68.0-78.3) in internal test cohort, 0.862 (95%CI 81.7-90.7),0.83 (95%CI 76.4-89.6),and 0.819(95%CI 74.6-89.2) in external test cohort. Conclusion: The nomograms that have been suggested demonstrate strong predictive capability. These tools can assist medical professionals in assessing the prognosis of patients with dCCA and in devising more accurate treatment strategies for them. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to analyze the impact of primary tumor resection (PTR) on the prognosis of four common primary tumors with liver metastases, and to develop a prognostic model to visualize the PTR benefit rate of patients with liver metastases. Materials and Methods: Patients diagnosed with colorectal cancer liver metastases (CRLM), pancreatic cancer liver metastases (PLM), gastric cancer liver metastases (GLM), and breast cancer liver metastases (BLM) between 2004 and 2015 were retrospectively reviewed from the Surveillance, Epidemiology, and End Results (SEER) database and assigned to either the surgery or non-surgery groups. A 1:1 propensity score matching (PSM) was performed. Surgical patients who survived longer than the median cancer-specific survival (CSS) time for non-surgery patients constituted the benefit group. Logistic regression was conducted to explore the independent factors affecting surgical benefit, and a nomogram was established. Results: A total of 21,928 patients with liver metastases were included. After PSM for surgery and non-surgery patients, we found that PTR had a significant impact on the overall survival (OS) and CSS of CRLM, PLM, and BLM patients. In CRLM patients, age (p < 0.001), primary site (p = 0.006), grade (p = 0.009), N stage (p = 0.034), and histology (p = 0.006) affected the surgical benefit. In BLM patients, the independent factors were age (p = 0.002), race (p = 0.020), and radiotherapy (p = 0.043). And in PLM patients, chemotherapy was an independent factor associated with a survival benefit from PTR. Conclusion: PTR improved OS and CSS in patients with CRLM, PLM, and BLM. A predictive model was established to identify suitable candidates for PTR in CRLM patients. [ABSTRACT FROM AUTHOR]