Occurrence Of Distant Metastases Research Articles

Development and validation of nomograms based on the SEER database for the risk factors and prognosis of distant metastasis in gastric signet ring cell carcinoma.

Poor prognosis in patients with distant metastasis of gastric signet ring cell carcinoma (GSRC), and there are few studies on the development and validation of the diagnosis and prognosis of distant metastasis of GSRC. The Surveillance, Epidemiology, and End Results database was used to identify patients with GSRC from 2004 to 2019. Univariate and multivariate logistic regression analysis were used to identify independent risk factors for distant metastasis of GSRC, while univariate and multivariate Cox proportional hazard regression analysis were used to determine independent prognostic factors for patients with distant metastasis of GSRC. Two nomograms were established, and model performance was evaluated using receiver operating characteristic curves, calibration plots, and decision curve analysis. A total of 9703 cases with GSRC were enrolled, among which 2307 cases (23.78%) were diagnosed with distant metastasis at the time of diagnosis. Independent risk factors for distant metastasis included age, race, and T stage. Independent prognostic factors included T stage, chemotherapy, and surgery. The receiver operating characteristic curve, calibration curve, decision curve analysis curve, and Kaplan-Meier survival curve of the training set and validation set confirmed that the 2 nomograms could accurately predict the occurrence and prognosis of distant metastasis in GSRC. Two nomograms can serve as effective prediction tools for predicting distant metastasis in GSRC patients and the prognosis of patients with distant metastasis. They have a certain clinical reference value.

Evaluation of peripheral blood inflammation indexes as prognostic markers for colorectal cancer metastasis

The aim of this study was to evaluate the prognostic value of peripheral blood inflammation indexes in patients with metastatic Colorectal Cancer (CRC) and to establish a predictive scoring system. A total of 324 CRC patients diagnosed through pathological examination from January 2017 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were included. The prognosis of patients with metastatic CRC was examined, and the correlation between IL-10 expression in pathological tissues and IL-10 expression in serum was analyzed. The results showed that the prognosis of CRC was poorer when metastasis occurred (P < 0.001). Additionally, IL-10 was highly expressed in the metastatic CRC group (P = 0.018), and the expression of IL-10 in pathological tissues of patients with metastatic CRC was positively correlated with the expression of IL-10 in serum (P = 0.037). The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-white blood cell ratio (LWR), aggregate index of systemic inflammation (AISI), monocyte-to-lymphocyte ratio (MLR), systemic inflammatory response index (SIRI), prognostic nutritional index (PNI), advanced lung cancer inflammation index (ALI), and interleukin-10 (IL-10) were calculated and determined by ROC curve. The critical values were 2.135, 3.735, 353.745, 0.265, 1.025, 52.975, 353.635, and 11.25, respectively. Inflammatory indexes with an AUC of more than 0.6 were selected, and each colorectal cancer patient with any of these risk factors was assigned a score of one. The 324 patients were then divided into two groups: 0–4 for the low-risk group and 4–8 for the high-risk group. The occurrence of distant metastases in the two groups was statistically analyzed. The results showed that the OS and PFS of the low-risk group were significantly superior to those of the high-risk group (P < 0.05). These findings indicate that NLR, LWR, AISI, MLR, SIRI, PNI, ALI, and IL-10 are risk factors for distant metastasis in CRC patients. Therefore, the prediction scores of these indexes can be used to effectively evaluate the prognosis of patients with metastatic CRC.

Contribution of PKS+ Escherichia coli to colon carcinogenesis through the inhibition of exosomal miR-885-5p

ObjectivesAbout 90 % of all colorectal cancer (CRC) fatalities are caused by the metastatic spread of primary tumors, which is closely correlated with patient survival and spreads by circulating tumor cells (CTCs). The epithelial-mesenchymal transition (EMT) that characterizes CTCs is associated with a poor prognosis. Organotropic metastasis is dictated by the transmission of miRNAs by cancer-derived exosomes. The purpose of this research is to examine PKS + E's function. Coli in CRC metastases and exosomal miR-885-5p suppression. MethodsA cohort of 100 patients (50 CRC, 50 healthy) underwent colonoscopy screenings from February 2018 to August 2021. Exosomes were isolated using ultracentrifugation, and exosomal miRNA was analyzed using sequencing and qPCR. ResultsAmong the patients, 40 tested positive for E. coli (12 CRC, 23 healthy). Serotyping revealed that 68.57 % harbored the PKS gene. Exosomal miR-885-5p levels were significantly altered in CRC patients with PKS + E. coli. Intriguingly, our findings indicate that exosomes derived from EMT-CRC cells did not affect miR-885-5p synthesis in HUVECs. Moreover, we observed that the levels of miR-885-5p in both exosomes and the total CRC-conditioned medium were comparable upon isolation of exosomes from CRC cells. What's more, an increased expression of miR-558-5p within the tumors, and the group that received exosome treatment, as well as the EMT-HCT116 group, exhibited a higher occurrence of distant metastasis. ConclusionPKS + E. By inhibiting exosomal miR-885-5p, coli is linked to CRC metastases, offering a possible target for therapeutic intervention.

Development and validation of an artificial intelligence model for predicting de novo distant bone metastasis in breast cancer: a dual-center study

ObjectiveBreast cancer has become the most prevalent malignant tumor in women, and the occurrence of distant metastasis signifies a poor prognosis. Utilizing predictive models to forecast distant metastasis in breast cancer presents a novel approach. This study aims to utilize readily available clinical data and advanced machine learning algorithms to establish an accurate clinical prediction model. The overall objective is to provide effective decision support for clinicians.MethodsData from 239 patients from two centers were analyzed, focusing on clinical blood biomarkers (tumor markers, liver and kidney function, lipid profile, cardiovascular markers). Spearman correlation and the least absolute shrinkage and selection operator regression were employed for feature dimension reduction. A predictive model was built using LightGBM and validated in training, testing, and external validation cohorts. Feature importance correlation analysis was conducted on the clinical model and the comprehensive model, followed by univariate and multivariate regression analysis of these features.ResultsThrough internal and external validation, we constructed a LightGBM model to predict de novo bone metastasis in newly diagnosed breast cancer patients. The area under the receiver operating characteristic curve values of this model in the training, internal validation test, and external validation test1 cohorts were 0.945, 0.892, and 0.908, respectively. Our validation results indicate that the model exhibits high sensitivity, specificity, and accuracy, making it the most accurate model for predicting bone metastasis in breast cancer patients. Carcinoembryonic Antigen, creatine kinase, albumin-globulin ratio, Apolipoprotein B, and Cancer Antigen 153 (CA153) play crucial roles in the model’s predictions. Lipoprotein a, CA153, gamma-glutamyl transferase, α-Hydroxybutyrate dehydrogenase, alkaline phosphatase, and creatine kinase are positively correlated with breast cancer bone metastasis, while white blood cell ratio and total cholesterol are negatively correlated.ConclusionThis study successfully utilized clinical blood biomarkers to construct an artificial intelligence model for predicting distant metastasis in breast cancer, demonstrating high accuracy. This suggests potential clinical utility in predicting and identifying distant metastasis in breast cancer. These findings underscore the potential prospect of developing economically efficient and readily accessible predictive tools in clinical oncology.

Association of residual ductal carcinoma in situ with breast cancer treatment outcomes after neoadjuvant chemotherapy according to hormone receptor status

PurposeThis research aimed to clarify the impact of residual ductal carcinoma in situ(DCIS) in surgical specimens obtained after neoadjuvant chemotherapy(NAC) for breast cancer on the associated prognosis outcomes.MethodsThis retrospective study was performed on a cohort of 1,009 patients who achieved pCR following NAC for breast cancer and underwent subsequent breast surgery at a single institution between January 2008 and December 2019. Overall survival, local recurrence-free survival, distant metastasis-free survival, and disease-free survival of the residual and non-residual DCIS groups were the outcomes compared, with further subgroup analysis performed according to hormone receptor status. Results260 individuals (25.8%) presented with residual DCIS. Based on a median follow-up of 54.0 months, no significant differences in outcomes were observed between the two groups. Patients with residual DCIS and hormone receptor-negative (HR-) breast cancer demonstrated a significant decrease in distant metastasis-free survival (p = 0.030) compared to those without residual DCIS. In the HR + cohort, no significant difference was observed between the two groups. Multivariate analysis of the HR- cohort demonstrated a significant association between residual DCIS and an elevated risk for distant recurrence (hazard ratio = 2.3, 95% confidence interval = 1.01–5.20, p = 0.047).ConclusionsResidual DCIS following NAC may impact breast cancer outcomes, particularly with respect to the occurrence of distant metastasis in HR- patients. Therefore, clinicians must vigilantly monitor patients with residual DCIS after NAC, and further research is needed to expand our understanding of the clinical implications of residual DCIS.

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.

Genome-wide CRISPR screening identifies the pivotal role of ANKRD42 in colorectal cancer metastasis through EMT regulation.

Colorectal cancer (CRC), a pervasive and lethal malignancy of gastrointestinal cancer, imposes significant challenges due to the occurrence of distant metastasis in advanced stages. Understanding the intricate regulatory mechanisms driving CRC distant metastasis is of paramount importance. CRISPR-Cas9 screening has emerged as a powerful tool for investigating tumor initiation and progression. However, its application in studying CRC distant metastasis remains largely unexplored. To establish a model that faithfully recapitulates CRC liver metastasis in patients, we developed an in vivo genome-wide CRISPR-Cas9 screening approach using a spleen-injected liver metastasis mouse model. Through comprehensive screening of a whole-genome sgRNA library, we identified ANKRD42 as a pivotal regulatory gene facilitating CRC liver metastasis. Analysis of the TCGA database and our clinical cohorts unveiled heightened ANKRD42 expression in metastases. At the cellular level, the attenuation of ANKRD42 impaired the migration and invasion processes of tumor cells. In vivo experiments further validated these observations, highlighting the diminished liver metastatic capacity of tumor cells upon ANKRD42 knockdown. To unravel the specific mechanisms by which ANKRD42 regulates CRC distant metastasis, we leveraged patient-derived organoid (PDO) models. Depleting ANKRD42 in PDOs sourced from liver metastases precipitated the downregulation of pivotal genes linked to epithelial-mesenchymal transition (EMT), including CDH2 and SNAI2, thereby effectively suppressing tumor metastasis. This study not only establishes a conceptual framework but also identifies potential therapeutic avenues for advanced-stage distant metastasis in CRC patients.

Uveal melanoma incidence and survival analysis in Portugal between 2013 and 2022

PurposeThis study aims to provide a comprehensive overview of the clinical characteristics and epidemiology of uveal melanoma (UM) in the Portuguese population, evaluated at the National Reference Centre (NRC). MethodsA prospective observational study was conducted, involving patients consecutively diagnosed with UM at the Portuguese NRC between July 2013 and December 2022. The study collected data on demographic and tumour characteristics, clinical staging according to the American Joint Committee on Cancer (AJCC), treatment approaches, local disease control, patient survival, and the occurrence of distant metastases. ResultsThe study included a total of 316 patients, 53.8% female. The mean age at diagnosis was 61.8±14.2 years, and 75.0% of patients presented with symptoms. The mean annual age-adjusted incidence of uveal melanoma in Portugal between 2014 and 2022 was 2.4 cases per million (95% confidence interval [CI]: 2.1–2.8). For choroidal/ciliary body tumours, the overall cumulative survival and distant metastases-free survival (DMFS) rates at 5 years were 84.9% (95% CI: 78.7–91.1) and 79.4% (95%CI: 72.8–86.0), respectively. Notably, higher AJCC stages at presentation, the need for enucleation, and increased tumour thickness were associated with lower DSS and DMFS rates. ConclusionThis study represents the most extensive analysis of UM epidemiology within the Portuguese population. The findings underscore the importance of early diagnosis and treatment in UM, as lower AJCC stages and smaller tumour thickness at diagnosis correlate with improved DSS and DMFS.

Application of interpretable machine learning algorithms to predict distant metastasis in ovarian clear cell carcinoma.

Ovarian clear cell carcinoma (OCCC) represents a subtype of ovarian epithelial carcinoma (OEC) known for its limited responsiveness to chemotherapy, and the onset of distant metastasis significantly impacts patient prognoses. This study aimed to identify potential risk factors contributing to the occurrence of distant metastasis in OCCC. Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients diagnosed with OCCC between 2004 and 2015. The most influential factors were selected through the application of Gaussian Naive Bayes (GNB) and Adaboost machine learning algorithms, employing a Venn test for further refinement. Subsequently, six machine learning (ML) techniques, namely XGBoost, LightGBM, Random Forest (RF), Adaptive Boosting (Adaboost), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were employed to construct predictive models for distant metastasis. Shapley Additive Interpretation (SHAP) analysis facilitated a visual interpretation for individual patient. Model validity was assessed using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the receiver operating characteristic curve (AUC). In the realm of predicting distant metastasis, the Random Forest (RF) model outperformed the other five machine learning algorithms. The RF model demonstrated accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and AUC (95% CI) values of 0.792 (0.762-0.823), 0.904 (0.835-0.973), 0.759 (0.731-0.787), 0.221 (0.186-0.256), 0.974 (0.967-0.982), 0.353 (0.306-0.399), and 0.834 (0.696-0.967), respectively, surpassing the performance of other models. Additionally, the calibration curve's Brier Score (95%) for the RF model reached the minimum value of 0.06256 (0.05753-0.06759). SHAP analysis provided independent explanations, reaffirming the critical clinical factors associated with the risk of metastasis in OCCC patients. This study successfully established a precise predictive model for OCCC patient metastasis using machine learning techniques, offering valuable support to clinicians in making informed clinical decisions.

Abstract 4129: Mitochondria-targeted antioxidant MitoQ inhibits human breast cancer metastasis in mice

Abstract In oncology, the occurrence of distant metastases often marks the transition from curative to palliative care. Such outcome is highly predictable for triple-negative and HER2-positive breast cancer patients, even if tumors are detected early, and there is no treatment to prevent metastasis. Here, considering that mitochondria are bioenergetic sensors of the tumor microenvironment, we report in preclinical mouse models that human breast cancer relapse is not a fatality: local recurrence and metastatic dissemination can be prevented by MitoQ, a mitochondria-targeted antioxidant that already underwent Phase I safety and Phase II efficacy trials in humans for pathologies other than cancer. Metastatic prevention was confirmed in the MMTV-PyMT model of spontaneously metastatic mouse breast cancer. After oral delivery, MitoQ was effective at nanomolar concentrations at which nonmalignant cells were spared. In anticipation of future clinical trials, a robust signature of the response to MitoQ was defined, applicable to bulk primary tumor biopsies. Citation Format: Tania Capeloa, Pierre Sonveaux. Mitochondria-targeted antioxidant MitoQ inhibits human breast cancer metastasis in mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4129.

Development and validation of a nomogram model for predicting distant metastasis of aged ≥50 patients with thyroid carcinoma: a SEER database analysis.

This work aimed to construct and validate a model for predicting distant metastasis (DM) in thyroid carcinoma (TC) patients aged≥50. The research data were collected from the Surveillance, Epidemiology, and End Results (SEER) program databases via SEER*Stat software (https://seer.cancer.gov/). Logistics regression was used to screen the independent risk factors for TC patients. The nomogram was constructed and validated based on the logistics regression results for predicting DM occurrence in TC patients. Moreover, the characteristic curves (ROC) were used to assess the predictive performance. The decision analysis curve (DCA) and the calibration curve were used to test this nomogram's accuracy and discrimination. Additionally, we analyzed survival and risk scores in TC patients with metastasis using the Kaplan-Meier (KM) method. A total of 11,166 TC patients were divided into a training set and a validation set. The results showed that topography (T), lymph node metastasis (N), and (grade) G were crucial risk factors for predicting DM. ROC analysis showed that the model had a good discriminative ability both in the training and validation set. The DCA curve showed greater net benefits across a range of DM risks for the nomogram in the training and validation set. Survival analyses showed that the metastasis cases with low-risk scores have shown a poorer prognosis in this study, both in the training and validation set. The nomogram model had excellent predictive performance and net benefit for predicting DM of TC patients aged ≥50. The model can help doctors develop treatment plans for their patients.

Nonoperative, Active Surveillance of Larger Malignant and Suspicious Thyroid Nodules.

Active surveillance for papillary thyroid cancer (PTC) meeting criteria for surgical resection is uncommon. Which patients may prove reasonable candidates for this approach is not well defined. This work aimed to examine the feasibility and safety of active surveillance for patients with known or suspected intrathyroidal PTC up to 4 cm in diameter. A retrospective review was conducted of all consecutive patients who underwent nonoperative active surveillance of suspicious or malignant thyroid nodules over a 20-year period from 2001 to 2021. We included patients with an initial ultrasound-fine-needle aspiration confirming either (a) Bethesda 5 or 6 cytology or (b) a "suspicious" Afirma molecular test. The primary outcomes and measures included the rate of adverse oncologic outcomes (mortality and recurrence), as well as the cumulative incidence of size/volume growth. Sixty-nine patients were followed with active surveillance for 1 year or longer (average 55 months), with 26 patients (38%) having nodules 2 cm or larger. No patients were found to develop new-incident occurrence of lymph node or distant metastasis. One patient, however, demonstrated concern for progression to a dedifferentiated cancer on repeat core biopsy 17 years after initial start of nonoperative selection. A total of 21% of patients had an increase in maximum diameter more than 3 mm, while volume increase of 50% or greater was noted in 25% of patients. Thirteen patients ultimately underwent delayed (rescue) surgery, and no disease recurrence was noted after such treatment. Age and initial nodule size were not predictors of nodule growth. These data expand consideration of active surveillance of PTC in select patients with intrathyroidal suspected malignancy greater than 1 cm in diameter. Rescue surgery, if required at a later time point, appears effective.

Metastatic profiles and survival differences between infiltrating ductal carcinoma and infiltrating lobular carcinoma in invasive breast cancer

BackgroundIn this study, we conducted a comprehensive evaluation of metastatic profiles and survival outcomes in patients with infiltrating ductal carcinoma (IDC) and infiltrating lobular carcinoma (ILC) treated at our university hospital center. MethodsWe collected and analyzed data from all patients diagnosed with invasive breast cancer at our center between January 1, 2007, and 31 December 2014. We specifically compared three subgroups: patients with IDC, patients with ILC and patients with mixed carcinoma, which is a combination of IDC and ILC. ResultsAmong the 1963 patients treated for invasive breast cancer in our center during the study period, 1435 had IDC, 466 had ILC, and 59 had mixed carcinoma. The incidence of patients with at least one positive axillary lymph node differed significantly: 40 % for IDC, 36 % for ILC, and 45 % for mixed carcinoma (p = 0.001). However, there was no significant difference in the mean number of positive nodes (p = 0.1633). The occurrence of distant metastases was lower in patients with ILC (p = 0.04), particularly in the case of brain metastases (p = 0.01), although there was no difference in bone or visceral metastatic sites. Patients with ILC exhibited a longer mean time to metastasis from the initial diagnosis of invasive breast carcinoma. Overall survival (p = 0.0525) and survival without locoregional recurrence (p = 0.026) were significantly different. Specifically, the 5-year overall survival rates for IDC, ILC, and mixed carcinoma were approximately 95 %. Distance metastatic-free survival at 5 years was 85 % for IDC, 91 % for ILC, and 87 % for mixed carcinoma (p = 0.00506). ConclusionOur findings indicate variations in the distribution of distant metastatic sites among patients with IDC, ILC, and mixed carcinoma, as well as differences in survival outcomes. This study sheds light on the unique characteristics and clinical implications associated with these two distinct subtypes of invasive breast cancer.

Early prediction of long-term survival of patients with nasopharyngeal carcinoma by multi-parameter MRI radiomics

PurposeThe objective is to create a comprehensive model that integrates clinical, semantic, and radiomics features to forecast the 5-year progression-free survival (PFS) of individuals diagnosed with non-distant metastatic Nasopharyngeal Carcinoma (NPC). MethodsIn a retrospective analysis, we included clinical and MRI data from 313 patients diagnosed with primary NPC. Patient classification into progressive and non-progressive categories relied on the occurrence of recurrence or distant metastasis within a 5-year timeframe. Initial screening comprised clinical features and statistically significant image semantic features. Subsequently, MRI radiomics features were extracted from all patients, and optimal features were selected to formulate the Rad-Score.Combining Rad-Score, image semantic features, and clinical features to establish a combined model Evaluation of predictive efficacy was conducted using ROC curves and nomogram specific to NPC progression. Lastly, employing the optimal ROC cutoff value from the combined model, patients were dichotomized into high-risk and low-risk groups, facilitating a comparison of 10-year overall survival (OS) between the groups. ResultsThe combined model showcased superior predictive performance for NPC progression, reflected by AUC values of 0.84, an accuracy rate of 81.60%, sensitivity at 0.77, and specificity at 0.81 within the training group. In the test set, the AUC value reached 0.81, with an accuracy of 74.6%, sensitivity at 0.82, and specificity at 0.66. ConclusionThe amalgamation of Rad-Score, clinical, and imaging semantic features from multi-parameter MRI exhibited significant promise in prognosticating 5-year PFS for non-distant metastatic NPC patients. The combined model provided quantifiable data for informed and personalized diagnosis and treatment planning.

Diagnostic challenges in low-grade central osteosarcoma.

Low-grade central osteosarcoma (LGCOS), a rare type of osteosarcoma, often has misleading radiological and pathological features that overlap with those of other bone tumours, thereby complicating diagnosis and treatment. We aimed to analyze the clinical, radiological, and pathological features of patients with LGCOS, with a focus on diagnosis, treatment, and outcomes. We retrospectively analyzed the medical records of 49 patients with LGCOS (Broder's grade 1 to 2) treated between January 1985 and December 2017 in a single institute. We examined the presence of malignant features on imaging (periosteal reaction, cortical destruction, soft-tissue invasion), the diagnostic accuracy of biopsy, surgical treatment, and oncological outcome. Based on imaging, 35 of 49 patients (71.4%) exhibited malignant features. Overall, 40 of 49 patients (81.6%) had undergone a biopsy before en-bloc resection: 27 of 40 patients (67.5%) were diagnosed on the first biopsy, which was more accurate when carried out by open rather than needle biopsy (91.3% vs 35.3% diagnostic accuracy, respectively; p < 0.001). Of the 40 patients treated by en-bloc resection, surgical margins were wide in 38 (95.0%) and marginal in two (5.0%). Furthermore, nine of 49 patients (18.4%) underwent curettage (intralesional margin) without previous biopsy. All patients with a positive margin developed local recurrence. Distant metastases occurred in five of 49 patients (10.2%). The mean five-year overall survival (OS) and distant relapse-free survival (D-RFS) were 89.3% (SD 5.1%) and 85.7% (SD 5.5%), respectively. Univariate analysis showed that the occurrence of distant metastasis was a poor prognostic factor for OS (hazard ratio 11.54, 95% confidence interval (CI) 1.92 to 69.17; p < 0.001). Local recurrence was a poor prognostic factor for D-RFS (HR 8.72, 95% CI 1.69 to 45.0; p = 0.002). The diagnosis of LGCOS can be challenging because it may present with non-malignant features and has a low diagnostic accuracy on biopsy. If precisely diagnosed, LGCOS can be successfully treated by surgical excision with wide margins.

Total neoadjuvant therapy for each locally advanced rectal cancer?

SummaryThe treatment paradigm for locally advanced rectal cancer has changed in recent years. Neoadjuvant radiochemotherapy followed by total mesorectal excision and postoperative chemotherapy has been the standard of care since many years. With this multidisciplinary approach the local recurrence rate is low, but the occurrence of distant metastases and impairments of quality of life due to bowel, bladder, and sexual dysfunction are still unresolved problems. The integration of induction or consolidation chemotherapy into the neoadjuvant setting, a watch-and-wait strategy without surgery for patients with clinical complete response, the integration of immunotherapy into the neoadjuvant setting in microsatellite-instable rectal cancer as well as the selective omission of neoadjuvant radiotherapy now represent different treatment options and enable individualization of therapy for locally advanced rectal cancer. Here, we provide an overview of the latest developments in the treatment of locally advanced rectal cancer and a discussion on which patients need more intensive or less intensive therapy.

Radioactive iodine therapy for follicular thyroid cancer: a 15 years follow-up study of Chinese patients.

To identify long-term predictors of distant metastases (DM) and the overall survival (OS) of follicular thyroid cancer (FTC) patients who underwent radioactive iodine (RAI) therapy. And to expand the knowledge about the clinical course and experience of RAI treatment for FTC. A total of 117 FTC patients who underwent RAI therapy at our institution from 2005 to 2020 were retrospectively studied. Patient characteristics, serum stimulating thyroglobulin (sTg) and thyroglobulin antibody levels, treatment process and follow-up data were collected until 26 April 2022. A total of 16 patients (13.7%) were lost to follow-up. A total of 23 (19.7%) patients with DM died and all FTC without DM were still alive. DM was seen in 58.4% (59/101) of patients. The most common location for metastatic lesions was the lung. Then was bone. The mean survival time of FTC with RAI was 156 months [95% confidence interval (CI): 142-171]. Five-year and 10-year cumulative survival rates of them were 88.8% and 67.4%, respectively. As for patients with DM were 80.4% and 41.3%, respectively. Age at diagnosis [odds ratio (OR) = 1.080, P = 0.009], RAI therapy sessions (OR = 2.959, P = 0.001) and sTg level (OR = 1.006, P = 0.002) were predictive of DM occurrence in FTC with RAI. In the group of FTC with DM, survival analysis showed that males were more likely to have a lower OS than females ( P = 0.039). Age, number of RAI therapy sessions, and sTg level were predictive of the occurrence of DM in FTC patients with RAI. Sex would influence the OS of FTC patients with DM.

Development and Validation of Nomograms to Predict Risk and Prognosis in Salivary Gland Carcinoma Patient with Distant Metastases.

Background: Salivary gland carcinoma (SGC) patients with distant metastasis (DM) are rare, and understanding this disease is insufficient. Nomograms can predict the prognostic probability of patients, while few studies have examined diagnostic and prognostic factors in SGC patients with DM. The purpose of this study was to establish and validate the risk and prognostic nomograms of SGC patients with DM. Methods: Based on the SEER database, we analyzed the data of SGC patients between 2004 and 2015. Logistic regression analyses and Cox proportional hazards regression analyses were used to identify risk and prognostic factors for DM in SGC patients. Based on the Akaike information criterion (AIC) value and likelihood ratio test, the best-fitting model was selected to build risk and prognostic nomograms, and the results were evaluated by receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and Kaplan-Meier (K-M) survival curves. ROC curves were also used to compare the nomograms with the American Joint Committee on Cancer (AJCC) staging system. Results: 7418 SGC patients were included in the study, and 307 (4.14%) of them were diagnosed with DM. This study identified that there are variables (age ≥ 80, no-parotid gland primary site, histologic type of mucoepidermoid carcinoma and squamous cell carcinoma, T stage ≥ T2, N staged ≥ N1, histologic grade ≥ III, and tumor size ≥ 41 mm) associated with the occurrence of DM in SGC patients. Therefore, we constructed diagnostic and prognostic nomograms after incorporating these variables. ROC curves illustrated the better predictive efficacy of 2 nomograms over the AJCC staging system. DCA curves, calibration curves, and K-M survival curves showed that 2 nomograms can accurately predict the occurrence and prognosis of DM among SGC patients in training and validation sets. Conclusion: It was shown that the nomograms were highly discriminative in predicting the diagnosis and prognosis of SGC patients with DM, and could identify high-risk patients, thereby providing SGC patients with individualized treatment plans.

Prevalence and oncologic impact of chronic kidney disease for upper tract urothelial carcinoma in endemic area

ObjectiveThis study aimed to assess the impact of preoperative chronic kidney disease (CKD) on the oncological outcomes of patients with upper tract urothelial carcinoma (UTUC) who underwent standard radical nephroureterectomy (RNU). MethodsA total of 1172 UTUC patients who received RNU at a single center in Taiwan between February 2005 and August 2019 were included. The patients were categorized into two groups based on their preoperative CKD stage: CKD stage ≤3 (811 patients) and CKD stage >3 (361 patients). The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) formula. The study investigated the oncological outcomes, including intravesical recurrence, non-urothelial recurrence, and cancer-specific mortality, stratified by preoperative CKD status. ResultsThe main findings indicated that UTUC patients with CKD stage >3 in Taiwan exhibited a higher proportion of females (p < 0.001), a greater history of concurrent bladder cancer (p = 0.003), more multifocal tumor behavior (p < 0.001), a higher incidence of carcinoma in situ (p = 0.008), increased rates of intravesical recurrence (p < 0.001), a lower prevalence of smoking history (p = 0.003), lower utilization of adjuvant chemotherapy (p < 0.001), reduced occurrence of non-urothelial recurrence (p < 0.001), and lower cancer-specific mortality (p = 0.006) compared to patients with CKD stage ≤3. Multivariate Cox regression analysis revealed significant differences in intravesical recurrence (p = 0.014) and non-urothelial recurrence (p = 0.006) between the CKD stage >3 and CKD stage ≤3 groups. The study also demonstrated that patients with concurrent bladder cancer and variant histology had higher rates of intravesical recurrence, non-urothelial recurrence, and cancer-specific mortality. The CKD stage >3 group exhibited lower rates of intravesical recurrence (p = 0.0014), higher rates of non-urothelial recurrence (p < 0.0001), and increased cancer-specific mortality (p = 0.0091) compared to the CKD stage ≤3 group in the 5-year free survival analysis. ConclusionIn Taiwan, UTUC patients with CKD stage >3 exhibit distinct characteristics compared to the general population with urothelial carcinoma. They are associated with a non-smoking status, a higher proportion of females, and less aggressive pathological features. Additionally, CKD stage >3 can serve as a clinical indicator for intravesical and non-urothelial recurrence. Further investigation into molecular aspects and treatment modifications for these patients is warranted.

Lymph Node Ratio as a Predictive Factor of Persistent/Recurrent Disease in Patients With Medullary Thyroid Cancer: A Single-Centre Retrospective Study

ObjectiveThyroidectomy with neck lymph node dissection is curative for most patients with medullary thyroid cancer (MTC). Lymph node ratio (LNR, ie, the ratio between the metastatic and the removed lymph nodes) is a reliable parameter with which to estimate both disease extent and quality of neck dissection. The aim of this study was to investigate the prognostic role of LNR to predict persistent/recurrent disease in patients with MTC. MethodsA single-center, retrospective study of a consecutive cohort of 95 patients with MTC treated with total thyroidectomy and neck dissection. Receiver operating characteristics curve analysis was performed to identify the LNR cut-off. ResultsLNR was positively associated with tumor size, preoperative and postoperative calcitonin values, postsurgery carcinoembryonic antigen values, persistent/recurrent disease, and the occurrence of distant metastases during follow-up. At multivariate analysis, persistent/recurrent disease was independently associated with the LNR value and was accurately predicted by a cut-off value of 0.12 (area under the curve = 0.85). Indeed, patients with LNR ≥0.12 had a higher probability of developing persistent/recurrent disease (79.3% vs 10.6%, odds ratio = 32.3, 95% CI = 9.8-106.4; P < .001) and distant metastasis (34.5% vs 3.0%, odds ratio = 16.8, 95% CI = 3.4-83.6; P < .001) than patients with LNR <0.12. The median time to progression was 15 months in patients with LNR ≥0.12 whereas it was not reached in patients with LNR <0.12 (hazard ratio: 7.18, 95% CI = 3.01-17.11, P < .001). ConclusionsLNR is a reliable prognostic factor to predict the risk of recurrence, persistence, and distant metastases in patients with MTC.