Surveillance for Distant Metastasis in Breast Cancer Patients Who Underwent Contemporary Management: A Report from the Korean Breast Cancer Society Survivor Research Group.

BACKGROUND: Current guidelines recommend against the use of routine imaging tests to detect distant metastasis in asymptomatic breast cancer patients. However, recent advancements in effective therapeutics and diagnostic accuracy have raised the need to reassess the clinical efficacy of intensive metastasis surveillance. We report the results of a multicenter retrospective study to investigate the association between intensive imaging studies and survival outcomes. PATIENTS AND METHODS: We retrospectively reviewed the data of 4130 patients who underwent surgery from 11 hospitals in Korea between January 2010 and December 2011. Patients were divided into two groups on the basis of the intensity of metastasis imaging studies during their disease-free period. The types and intervals of the imaging studies were based on each physician's decisions. RESULTS: High-intensive screening showed a shorter distant metastasis-free survival [p < 0.001, hazard ratio (HR) 1.62; 95% confidence interval (CI) 1.29-2.04], especially for patients in whom bone or lung was the first site of metastasis. With a median follow-up period of 110.0 months, the 5-year breast cancer-specific survival (BCSS) rate was 96.5%. The high-intensity screening group showed significantly poorer BCSS compared with the low-intensity screening group (p < 0.001, HR 3.13; 95% CI 2.32-4.21). However, both multivariable analysis and propensity score matching analysis showed no significant association between the screening intensity and BCSS. CONCLUSIONS: Frequent imaging studies to detect distant metastasis were associated with earlier detection of distant metastasis, especially for lung and bone metastasis. However, intensive surveillance showed no apparent association with BCSS despite the use of currently available treatments.

A nomogram combining neutrophil to lymphocyte ratio (NLR) and prognostic nutritional index (PNI) to predict distant metastasis in gastric cancer.

In this study, We aim to explore the association between the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), lymphocyte to monocyte ratio (LMR) and prognostic nutritional index (PNI) and distant metastasis of gastric cancer and develop an efficient nomogram for screening patients with distant metastasis. A total of 1281 inpatients with gastric cancer were enrolled and divided into the training and validation set.Univariate, Lasso regression and Multivariate Logistic Regression Analysis was used to identify the risk factors of distant metastasis. The independent predictive factors were then enrolled in the nomogram model. The nomogram's predictive perform and clinical practicality was evaluated by receiver operating characteristics (ROC) curves, calibration curves and decision curve analysis. Multivariate Logistic Regression Analysis identified D-dimer, CA199, CA125, NLR and PNI as independent predictive factors. The area under the curve of our nomogram based on these factors was 0.838 in the training cohort and 0.811 in the validation cohort. The calibration plots and decision curves demonstrated the nomogram's good predictive performance and clinical practicality in both training and validation cohort. Therefore,our nomogram could be an important tool for clinicians in screening gastric cancer patients with distant metastasis.

Development and validation of AI models using LR and LightGBM for predicting distant metastasis in breast cancer: a dual-center study.

Objective: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients. Methods: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models. Results: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase. Conclusion: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports.

BACKGROUND: Development of distant metastasis (DM) is a major concern during treatment of nasopharyngeal carcinoma (NPC). However, studies have demonstrated improved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy. Therefore, precise prediction of metastasis in patients with NPC is crucial. AIM: To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging (MRI) reports. METHODS: This retrospective study included 792 patients with non-distant metastatic NPC. A total of 469 imaging variables were obtained from detailed MRI reports. Data were stratified and randomly split into training (50%) and testing sets. Gradient boosting tree (GBT) models were built and used to select variables for predicting DM. A full model comprising all variables and a reduced model with the top-five variables were built. Model performance was assessed by area under the curve (AUC). RESULTS: Among the 792 patients, 94 developed DM during follow-up. The number of metastatic cervical nodes (30.9%), tumor invasion in the posterior half of the nasal cavity (9.7%), two sides of the pharyngeal recess (6.2%), tubal torus (3.3%), and single side of the parapharyngeal space (2.7%) were the top-five contributors for predicting DM, based on their relative importance in GBT models. The testing AUC of the full model was 0.75 (95% confidence interval [CI]: 0.69-0.82). The testing AUC of the reduced model was 0.75 (95%CI: 0.68-0.82). For the whole dataset, the full (AUC = 0.76, 95%CI: 0.72-0.82) and reduced models (AUC = 0.76, 95%CI: 0.71-0.81) outperformed the tumor node-staging system (AUC = 0.67, 95%CI: 0.61-0.73). CONCLUSION: The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC. The number of metastatic cervical nodes was identified as the principal contributing variable.

Clinicopathological spectrum, management, and outcome of ectopic parathyroid carcinoma: Experience with 24 cases.

PURPOSE: Ectopic parathyroid carcinoma (EPC) is a rare clinical entity with multiple diagnostic pitfalls, making surgical cures challenging. We assessed the clinicopathological spectrum and outcome of EPCs. METHODS: In this retrospective cohort study, 24 EPCs were identified from 133 PC patients treated at a tertiary referral center. The relationship between clinicopathological findings and locations was analyzed. RESULTS: The locations of EPCs were predominantly intrathyroidal (62.5%), followed by 16.7% in the mediastinum, 8.3% in the retropharyngeal space, 8.3% in the carotid sheath, and 4.2% in the upper neck. Intrathyroidal EPC patients experienced higher serum calcium (p = 0.020), a higher rate of vascular invasion (p = 0.040), and a slightly higher incidence of non-R0 initial resection (p = 0.092) than those in other ectopic locations. Intrathyroidal EPC patients also suffered a trend of higher upper aerodigestive tract (UAT) invasion rate (p = 0.070) and higher risks of distant metastasis (p = 0.037) than the other PC patients. The 5-year disease-free survival rate after surgery was slightly compromised at 41.5% in intrathyroidal EPC patients compared with 77.8% among those in other ectopic locations (p = 0.143) and 59.7% among the other PC patients (log-rank = 3.194; p = 0.074), though without statistical significance. CONCLUSION: Intrathyroidal EPC might cause a more biochemically and invasively distinct PC picture compared with other PCs. Special caution should be exercised in the preoperative diagnosis and management of such cases.

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning methods on the Surveillance, Epidemiology, and End Results (SEER) database to forecast the risk probability of distant metastasis. Therefore, the information on UM patients from the SEER database (2000-2020) was split into a 7:3 ratio training set and an internal test set based on distant metastasis presence. Univariate and multivariate logistic regression analyses assessed distant metastasis risk factors. Six machine learning methods constructed a predictive model post-feature variable selection. The model evaluation identified the multilayer perceptron (MLP) as optimal. Shapley additive explanations (SHAP) interpreted the chosen model. A web-based calculator personalized risk probabilities for UM patients. The results show that nine feature variables contributed to the machine learning model. The MLP model demonstrated superior predictive accuracy (Precision = 0.788; ROC AUC = 0.876; PR AUC = 0.788). Grade recode, age, primary site, time from diagnosis to treatment initiation, and total number of malignant tumors were identified as distant metastasis risk factors. Diagnostic method, laterality, rural-urban continuum code, and radiation recode emerged as protective factors. The developed web calculator utilizes the MLP model for personalized risk assessments. In conclusion, the MLP machine learning model emerges as the optimal tool for predicting distant metastasis in UM patients. This model facilitates personalized risk assessments, empowering early and tailored treatment strategies.

Children and adolescents with differentiated thyroid cancer from 1998 to 2018: a retrospective analysis.

OBJECTIVES: This study aims to investigate the clinical features of differentiated thyroid carcinoma (DTC) in children and adolescents under 18 years and assess the impact of surgery combined with thyroid hormone and radioactive iodine (RAI) on their prognosis. METHODS: A retrospective observational study was conducted, involving children/adolescents with DTC who underwent surgery at the Head and Neck Department of Tianjin Medical University Cancer Institute and Hospital from January 1998 to December 2018. RESULTS: Among 198 patients, 130 (65.7 %) were female. According to the American Thyroid Association guidelines, cases were categorized as low (106, 53.5 %), intermediate (54, 27.3 %), and high (38, 19.2 %) risk. The follow-up duration ranged from 3 to 23 years. Local recurrence and distant metastasis were identified in 21 (10.6 %) and 14 (7.1 %) cases, respectively. All patients received levothyroxine, while RAI therapy was administered to intermediate- and high-risk patients. The local recurrence and distant metastasis rates in these two groups were 33.3 and 39.5 %, respectively, with no recurrence or metastasis in the low-risk group. Persistent without structural evidence of disease were 0.9, 3.7, and 26.3 % at end of follow-up for the low-, intermediate-, and high-risk groups, respectively. The overall survival rates for all three groups were 100 %, while disease-free survival rates were 99.1, 63.0, and 34.2 % for the low-, intermediate-, and high-risk groups, respectively. CONCLUSIONS: Children/adolescents with low-risk DTC exhibited a favorable prognosis even without RAI. However, intermediate- and high-risk DTC patients, despite RAI and levothyroxine treatment, showed elevated rates of persistent disease, local recurrence, and distant metastasis.

Development of a novel dynamic nomogram for predicting overall survival in anaplastic thyroid cancer patients with distant metastasis: a population-based study based on the SEER database.

Background: Anaplastic thyroid cancer (ATC) is highly invasive, prone to distant metastasis (DM), and has a very poor prognosis. This study aims to construct an accurate survival prediction model for ATC patients with DM, providing reference for comprehensive assessment and treatment planning. Methods: We extracted data of ATC patients with DM diagnosed between 2004 and 2019 from the SEER database, randomly dividing them into a training set and a validation set in a ratio of 7:3. Univariate and multivariate Cox regression analyses were sequentially performed on the training set to identify independent prognostic factors for overall survival (OS) and construct nomograms for 3-month, 6-month, and 8-month OS for ATC patients with DM based on all identified independent prognostic factors. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) curve analysis, and calibration curves were separately plotted on the training and validation sets to demonstrate the model's performance. Furthermore, patients were stratified into high- and low-risk groups based on their risk scores, and the Kaplan-Meier (KM) survival curves were used to illustrate the survival differences between the two groups. Results: A total of 322 patients were included in this study. Univariate and multivariate Cox regression analyses identified five independent prognostic factors for OS in ATC patients with DM: surgery, tumor size, age, chemotherapy, and radiotherapy. Nomograms for 3-month, 6-month, and 8-month OS were established based on these factors. The training set AUC values (3-month AUC: 0.767, 6-month AUC: 0.789, 8-month AUC: 0.795) and validation set AUC values (3-month AUC: 0.753, 6-month AUC: 0.798, 8-month AUC: 0.806) as well as the calibration curves demonstrated excellent applicability and accuracy of the model. Additionally, the DCA curves indicated substantial clinical net benefit of the model. The KM curves also confirmed the model's excellent stratification ability for patient OS. Conclusion: The nomogram developed in this study accurately predicts OS for ATC patients with DM. It can assist clinicians in formulating appropriate treatment strategies for these patients.

The role of neck dissection in management of patients with clinically apparent parotid metastatic melanoma - systematic review.

Patients with cutaneous melanoma with metastatic deposits in the parotid gland have poor prognosis due to the high risk of developing distant metastasis. In the era of effective immunotherapy, there is no consensus amongst head and neck surgeons about the extent of neck dissection required for patients presenting with clinically apparent parotid metastasis. This review aims to determine the incidence and pattern of occult neck disease for patients with parotid metastasis reported in literature to help guide clinicians on the extent of neck dissection required. The systematic review search was conducted using PubMed, EMBASE and Medline, using PRISMA guidelines. The inclusion criteria include cases treated with parotidectomy and neck dissection for patients with parotid melanoma metastasis. A narrative synthesis was carried out due to heterogeneity of studies. A total of 14 studies was included. We found no study reporting on outcomes with surgery and adjuvant immunotherapy in this cohort of patients. The incidence of distant metastasis reported was variable but remains high for patients with parotid metastasis. Patients with parotid and neck involvement have poorer prognosis than patients with parotid only metastatic disease. The effect and extent of neck dissection in patients with clinically apparent parotid nodes remains unclear in the era of effective immunotherapy. There is a need for further well-designed studies evaluating the outcomes for such patients following surgery and adjuvant immunotherapy.

The predictive value of LGR for distant metastasis-free survival in locally advanced rectal cancer patients.

Studies show that inflammation induced by cancer is a key factor in carcinogenesis. Here, we sought to assess the relationship between patients with locally advanced rectal cancer (LARC) and the lymphocyte to neutrophil granulocyte ratio (LGR) prior to neoadjuvant chemoradiotherapy (nCRT) and distant metastasis-free survival (DMFS). Using a receiver operating characteristic (ROC) analysis of 326 LARC patients who underwent total mesorectal excision (TME) surgery and neoadjuvant chemoradiotherapy, we were able to determine the ideal LGR cutoff value. We used the Kaplan-Meier method and univariate and multivariate Cox regression to study the clinical characteristics of LARC patients in comparison between the low LGR group and the high LGR group. DMFS analysis was one of the primary clinical variables examined. We discovered that the low LGR group of LARC patients had a longer DMFS than the high LGR group. The median duration of follow-up for LARC patients was 89.4 months, with a significantly lower DMFS observed in the high LGR group compared to the low LGR group. Multivariate Cox regression analysis revealed that LARC patients with low LGR levels, early ypTNM stages, and BRAF wild had longer DMFS. LGR prior to nCRT was a critical prognostic indicator that contributed extra predictive value beyond conventional clinicopathological characteristics to predict the outcome of LARC patients receiving neoadjuvant chemoradiotherapy followed by TME surgery.

Construction of a nomogram for predicting HNSCC distant metastasis and identification of EIF5A as a hub gene.

Patients with distant metastasis of head and neck squamous cell carcinoma (HNSCC) often have a poor prognosis. However, early diagnosis of distant metastasis is challenging in clinical practice, and distant metastasis is often only detected in the late stages of tumor metastasis through imaging techniques. In this study, we utilized data from HNSCC patients collected from the TCGA database. Patients were divided into distant metastasis and nonmetastasis groups based on the tumor-node-metastasis (TNM) stage. We analyzed the differentially expressed genes between the two groups (DM/non-M DEGs) and their associated lncRNAs and generated a predictive model based on 23 lncRNAs that were significantly associated with the occurrence of distant metastasis in HNSCC patients. On this basis, we built a nomogram to predict the distant metastasis of HNSCC patients. Moreover, through WGCNA and Cytoscape software analysis of DM/non-M DEGs, we identified the gene most closely related to HNSCC distant metastasis: EIF5A. Our findings were validated using GEO data; EIF5A expression was significantly increased in the tumor tissues of HNSCC patients with distant metastasis. We then predicted miRNAs that can directly bind to EIF5A via the TargetScan and miRWalk websites, intersected them with differentially expressed miRNAs in the two groups from the TCGA cohort, and identified the only overlapping miRNA, miR-424; we predicted the direct binding site of EIF5A and miR-424 via the miRWalk website. Immunohistochemistry further revealed high expression of EIF5A in the primary tumor tissue of HNSCC patients with distant metastasis. These results provide a new perspective for the early diagnosis of distant metastasis in HNSCC patients and the study of the mechanisms underlying HNSCC distant metastasis.

Two Cases of Distant Metastasis After Mastectomy for Breast Ductal Carcinoma In Situ.

While the prognosis for ductal carcinoma in situ (DCIS) of the breast is generally excellent, distant metastasis after appropriate local treatment is extremely rare. We experienced two cases of distant metastasis after mastectomy for breast ductal carcinoma in situ. In both cases, the surgical margins were negative, the sentinel nodes were negative for metastasis. The first case was a 67-year-old woman who developed lung metastases four years after mastectomy for high-grade DCIS. The second case was a 34-year-old woman with intermediate-grade DCIS who developed intraductal recurrence localized to the nipple two years after the initial nipple-sparing mastectomy and multiple lung and liver metastases six months later. Both cases developed distant metastases despite appropriate local treatment, without preceding or concurrent invasive local recurrence. Although the probability of distant recurrence is low, it is important to inform patients about the risk of recurrence.

Survival After Contralateral Axillary Metastasis in Breast Cancer.

BACKGROUND: Despite stage IV categorization, survival outcomes for breast cancer patients who experience contralateral axillary lymph node metastasis (CAM) remain uncertain. This study aimed to investigate the clinical outcomes for patients with metachronous CAM to provide insights into its prognosis and treatment recommendations. METHODS: This study retrospectively reviewed medical records of patients who underwent curative surgery for breast cancer and experienced CAM as the first site of distant metastasis (DM) during the follow-up period between January 2001 and April 2023. Survival outcomes of the CAM patients were compared with those of breast cancer patients with other DM via propensity score-matching (PSM). RESULTS: The study identified 40 breast cancer patients with metachronous CAM. The estimated 5-year overall survival (OS) was 39.6%, and the progression-free survival was 39.4%. The patients with CAM exhibited marginally better OS than the patients with DM (p = 0.071), but survival similar to that of the patients with isolated supraclavicular node recurrence (SCN) (p = 0.509). Moreover, matching of CAM with DM using two PSM models showed a consistently insignificant survival difference (hazard ratio [HR], 1.47; p = 0.124 vs. HR, 1.19; p = 0.542). Ipsilateral breast tumor recurrences (IBTRs) were experienced by 12 patients before or concurrently with the CAM. These patients exhibited significantly better survival than the remaining patients (HR, 0.28; p = 0.024). CONCLUSION: The breast cancer patients with CAM showed survival similar to that for the patients with DM, supporting the current stage IV classification of the CAM. However, CAM associated with IBTR exhibited superior survival outcomes, suggesting that this subset of CAM may benefit from treatments with curative intent.

Establishing subdivisions of M1 stage nasopharyngeal carcinoma based on decision tree classification: A multicenter retrospective study.

OBJECTIVES: To meet the demand for personalized treatment, effective stratification of patients with metastatic nasopharyngeal carcinoma (mNPC) is essential. Hence, our study aimed to establish an M1 subdivision for prognostic prediction and treatment planning in patients with mNPC. MATERIALS AND METHODS: This study included 1239 patients with mNPC from three medical centers divided into the synchronous mNPC cohort (smNPC, n = 556) to establish an M1 stage subdivision and the metachronous mNPC cohort (mmNPC, n = 683) to validate this subdivision. The primary endpoint was overall survival. Univariate and multivariate Cox analyses identified covariates for the decision-tree model, proposing an M1 subdivision. Model performance was evaluated using time-dependent receiver operating characteristic curves, Harrell's concordance index, calibration plots, and decision curve analyses. RESULTS: The proposed M1 subdivisions were M1a (≤5 metastatic lesions), M1b (>5 metastatic lesions + absent liver metastases), and M1c (>5 metastatic lesions + existing liver metastases) with median OS of 34, 22, and 13 months, respectively (p < 0.001). This M1 subdivision demonstrated superior discrimination (C-index = 0.698; 3-year AUC = 0.707) and clinical utility over those of existing staging systems. Calibration curves exhibited satisfactory agreement between predictions and actual observations. Internal and mmNPC cohort validation confirmed the robustness. Survival benefits from local metastatic treatment were observed in M1a, while immunotherapy improved survival in patients with M1b and M1c disease. CONCLUSION: This novel M1 staging strategy provides a refined approach for prognostic prediction and treatment planning in patients with mNPC, emphasizing the potential benefits of local and immunotherapeutic interventions based on individualized risk stratification.

Comparison of metastasis and prognosis between early-onset and late-onset hepatocellular carcinoma: A population-based study.

Background: While hepatocellular carcinoma (HCC) represents a highly heterogeneous disease with variable oncogenesis mechanisms and biological features, little is understood about differences in distant metastasis (DM) and prognosis between early-onset and late-onset HCC. This study defined early-onset disease as cancer diagnosed at age younger than 50 years and aimed to present a comprehensive analysis to characterize these disparities based on age. Methods: Information of HCC patients was retrospectively collected from the SEER database and our hospital. Patient demographics, tumor characteristics, and survival were compared between the two groups. A 1:1 propensity score matching (PSM) was adopted to adjust confounding factors. Logistic and cox analysis were utilized to explore risk factors of DM and prognosis, respectively. Besides, the survival differences were assessed by the Kaplan-Meier curve and log-rank test. Results: In total, 19187 HCC patients obtained from the SEER database and 129 HCC patients obtained from our own center were enrolled. Among 19187 patients with HCC, 3376 were identified in the matched cohort, including 1688 early-onset patients and 1688 late-onset patients. Compared with late-onset HCC, early-onset HCC was more likely to occur in female (25.2% vs. 22.9%, P = 0.030), have large tumors (>10.0 cm, 24.1% vs. 14.6%, P = 0.000), harbor poorly differentiated/undifferentiated cancers (17.0% vs. 14.0%, P = 0.003), present advanced clinical stage (T3+T4, 33.7% vs. 28.5%; N1, 9.2% vs. 6.7%; P = 0.000), and develop DM (13.0% vs. 9.5%, P = 0.000). After adjustment for confounders by PSM, we discovered that early-onset HCC remained an independent risk factor for DM. However, combined with Kaplan-Meier curve and cox analysis, early-onset HCC was an independent favorable predictor of survival. We validated these data on an independent cohort from our hospital. Conclusion: In this population-based study, despite developing DM more frequently, early-onset HCC exhibited a superior prognosis than late-onset HCC. Nevertheless, further research is warranted to understand the underlying aetiologic basis for the disparities.

Prognostic Evaluation of HER2-positive Early Breast Cancers Using Clinico-pathological Criteria.

Background/Aim: HER2-positive breast carcinomas (BCs) generally behave more aggressively and show higher cytological and histological grade than HER2-negative BCs. However, the clinical properties of HER2-positive early BCs have not been studied extensively. Hence, the therapeutic significance of neoadjuvant chemotherapy (NAC) for this BC remains debatable. Patients and Methods: We retrospectively examined the clinicopathological features of 94 HER2-positive early BCs who perioperatively received anti-HER2 drugs, without undergoing NAC prior to surgery. Results: The patients' five year-disease free survival (DFS) and overall survival (OS) rates were 95.6% and 100%, respectively. Univariate analysis demonstrated significant differences in distant metastasis-free survival (DMFS) between clinical and pathological tumor stages (T stages). Pathological T1 stage and clinical T1 stage tumors showed significantly higher DMSF than pT2-3 and cT2-3 (p=0.0002 and 0.0294). Multivariate analysis disclosed no significant differences in DFS, OS, and DMFS with respect to preoperative clinical tumor stage, patient age, type of surgery, postoperative therapy, and pathological factors. Recurrences occurred in nine patients: four (4.3%) and five (5.3%) patients showed local and distant recurrences, respectively. One patient with cT2 BC died of disease. Interestingly, four of the five BCs with distant recurrence pathologically demonstrated lymph vessel invasion. The prognoses of patients with HER2-positive stage cT1/2N0M0 BC were highly favorable. Conclusion: The indications for NAC in small, localized, and node-negative HER2-positive BC should be carefully assessed based on the presence of a larger tumor size, postoperative pathological evaluation of tumor size, and lymph vessel invasion.

Epidemiology of the non-head and neck sebaceous carcinoma and implications for distant metastasis screening.

Introduction: Extraocular sebaceous carcinoma (SC), particularly those outside the head and neck region, is rare and not well-described. Purpose: This study aimed to explore the epidemiology and identify the prognostic factors of non-head and neck SC, describe the possible relevant factors of distant metastasis, and provide implications for distant metastasis screening. Methods: Data from the 17 registries in the Surveillance, Epidemiology, and End Results database were retrospectively collected for patients with SC outside the head and neck from 2000 through 2020. Overall survival (OS) and disease-specific survival (DSS) were the primary endpoints. Survival analysis was conducted through Kaplan-Meier curves, and multivariate analysis was carried out using Cox proportional hazard models. Results: A total of 1,237 patients with SC outside the head and neck were identified. The mean age at diagnosis of the entire patient cohort was 67.7 years (30 to 90+ years), and the mean tumor size was 2.2 cm (0.1-16 cm). Patients with distant disease experienced the lowest OS (mean, 29.5 months) than those with localized disease and regional disease (p < 0.0001). Multivariate analysis revealed that age, tumor size, and stage were independent determinants of OS; age, stage, and primary site were independent determinants of DSS. Tumor grade and lymph node status had less prognostic value for survival. Undifferentiated tumors have a trend toward distant metastasis, especially those at the primary site of the trunk. Conclusion: The prognosis of the non-head and neck SC is excellent, while the survival of distant disease is very poor. Distant metastasis screening can be considered for undifferentiated tumors, especially those located in the trunk region with large tumor sizes.

Efficacy of metastatic lesion radiotherapy in patients with metastatic nasopharyngeal carcinoma: A multicenter retrospective study.

OBJECTIVE: We investigated the efficacy of metastatic lesion radiotherapy (MLRT) in patients with metastatic nasopharyngeal carcinoma (mNPC). MATERIALS AND METHODS: Patients with mNPC from three institutions were included in this study. Propensity score matching (PSM) was employed to ensure comparability between patient groups. Overall survival (OS) rates were assessed using the Kaplan-Meier method and compared using the log-rank test. Prognostic factors were identified using univariate and multivariate Cox hazard analyses. Subgroup analyses were conducted to assess the effects of MLRT on specific patient populations. RESULTS: We analyzed data from 1157 patients with mNPC. Patients who received MLRT had significantly better OS than those who did not, both in the original (28 vs. 21 months) and PSM cohorts (26 vs. 23 months). MLRT was identified as an independent favorable predictor of OS in multivariate analyses, with hazard ratios of 0.67. The subgroup analysis results indicated that radiotherapy effectively treated liver, lung, and bone metastatic lesions, particularly in patients with a limited tumor burden. Higher total radiation doses of MLRT (biologically effective dose (BED) ≥ 56 Gy) were associated with improved OS, while neither radiation technique nor dose fractionation independently influenced prognosis. CONCLUSIONS: MLRT offers survival advantages to patients diagnosed with mNPC. Patients with limited metastatic burden derive the most benefit from MLRT, and the recommended regimen for MLRT is a minimum BED of 56 Gy for optimal outcomes.

Deep learning radiomics-based prediction model of metachronous distant metastasis following curative resection for retroperitoneal leiomyosarcoma: a bicentric study.

BACKGROUND: Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of metachronous distant metastasis (MDM) among patients with retroperitoneal leiomyosarcoma (RLS). Thus, the purpose of this study was to develop and validate a preoperative contrast-enhanced computed tomography (CECT)-based deep learning radiomics model for predicting the occurrence of MDM in patients with RLS undergoing complete surgical resection. METHODS: A total of 179 patients who had undergone surgery for the treatment of histologically confirmed RLS were retrospectively recruited from two tertiary sarcoma centers. Semantic segmentation features derived from a convolutional neural network deep learning model as well as conventional hand-crafted radiomics features were extracted from preoperative three-phase CECT images to quantify the sarcoma phenotypes. A conventional radiomics signature (RS) and a deep learning radiomics signature (DLRS) that incorporated hand-crafted radiomics and deep learning features were developed to predict the risk of MDM. Additionally, a deep learning radiomics nomogram (DLRN) was established to evaluate the incremental prognostic significance of the DLRS in combination with clinico-radiological predictors. RESULTS: The comparison of the area under the curve (AUC) values in the external validation set, as determined by the DeLong test, demonstrated that the integrated DLRN, DLRS, and RS models all exhibited superior predictive performance compared with that of the clinical model (AUC 0.786 [95% confidence interval 0.649-0.923] vs. 0.822 [0.692-0.952] vs. 0.733 [0.573-0.892] vs. 0.511 [0.359-0.662]; both P < 0.05). The decision curve analyses graphically indicated that utilizing the DLRN for risk stratification provided greater net benefits than those achieved using the DLRS, RS and clinical models. Good alignment with the calibration curve indicated that the DLRN also exhibited good performance. CONCLUSIONS: The novel CECT-based DLRN developed in this study demonstrated promising performance in the preoperative prediction of the risk of MDM following curative resection in patients with RLS. The DLRN, which outperformed the other three models, could provide valuable information for predicting surgical efficacy and tailoring individualized treatment plans in this patient population. TRIAL REGISTRATION: Not applicable.

The preliminary analysis of lymphatic flow around the connective tissues surrounding SMA and SpA elucidates patients' oncological condition in borderline-resectable pancreatic cancer.

BACKGROUND: In pancreatic ductal adenocarcinoma (PDAC), invasion of connective tissues surrounding major arteries is a crucial prognostic factor after radical resection. However, why the connective tissues invasion is associated with poor prognosis is not well understood. MATERIALS AND METHODS: From 2018 to 2020, 25 patients receiving radical surgery for PDAC in our institute were enrolled. HyperEye Medical System (HEMS) was used to examine lymphatic flow from the connective tissues surrounding SMA and SpA and which lymph nodes ICG accumulated in was examined. RESULTS: HEMS imaging revealed ICG was transported down to the paraaortic area of the abdominal aorta along SMA. In pancreatic head cancer, 9 paraaortic lymph nodes among 14 (64.3%) were ICG positive, higher positivity than LN#15 (25.0%) or LN#18 (50.0%), indicating lymphatic flow around the SMA was leading directly to the paraaortic lymph nodes. Similarly, in pancreatic body and tail cancer, the percentage of ICG-positive LN #16a2 was very high, as was that of #8a, although that of #7 was only 42.9%. CONCLUSIONS: Our preliminary result indicated that the lymphatic flow along the connective tissues surrounding major arteries could be helpful in understanding metastasis and improving prognosis in BR-A pancreatic cancer.