The latest World Health Organization classification of breast tumors recommends diagnosing malignant phyllodes tumors (MPTs) when all 5 morphologic features are present: permeative borders, marked ...stromal cellularity, marked stromal cytologic atypia, ≥10 mitoses per 10 high-power fields (HPF), and stromal overgrowth. We assessed the performance of this recommendation to capture MPTs and features predictive of distant metastasis in a multi-institutional retrospective study. Of 65 MPTs, most cases had at least focally permeative borders (58, 89%), with marked stromal cellularity in 40 (61.5%), marked atypia in 38 (58.5%), ≥10 mitoses per 10 HPF in 50 (77%), and stromal overgrowth in 56 (86%). Distant metastases were observed in 20 (31%) patients (median follow-up 24.5 mo, 1 to 204). Only 13 of 65 (20%) cases had all 5 morphologic features, while only 7 of 20 (35%) cases with distant metastases had all 5 features. In univariate analysis, only marked stromal atypia (
P
=0.004) and cellularity (
P
=0.017) were associated with decreased distant metastasis-free survival. In multivariate Cox regression, the combination of stromal overgrowth, marked stromal cellularity, and atypia (C-index 0.721, 95% CI: 0.578, 0.863) was associated with decreased distant metastasis-free survival. The current World Health Organization recommendation will miss a significant number of MPTs with distant metastases. We propose refined diagnostic criteria for MPTs: (1) stromal overgrowth combined with ≥1 feature(s) (marked cellularity, marked atypia, or ≥10 mitoses per 10 HPF), or (2) in the absence of stromal overgrowth, marked cellularity combined with ≥1 feature(s) (permeative borders, marked atypia, or ≥10 mitoses per 10 HPF).
Background
Distant metastasis is the primary cause of treatment failure in locoregionally advanced nasopharyngeal carcinoma (LANPC).
Purpose
To develop a model to evaluate distant metastasis‐free ...survival (DMFS) in LANPC and to explore the value of additional chemotherapy to concurrent chemoradiotherapy (CCRT) for different risk groups.
Study Type
Retrospective.
Population
In all, 233 patients with biopsy‐confirmed nasopharyngeal carcinoma (NPC) from two hospitals.
Field Strength
1.5T and 3T.
Sequence
Axial T2‐weighted (T2‐w) and contrast‐enhanced T1‐weighted (CET1‐w) images.
Assessment
Deep learning was used to build a model based on MRI images (including axial T2‐w and CET1‐w images) and clinical variables. Hospital 1 patients were randomly divided into training (n = 169) and validation (n = 19) cohorts; Hospital 2 patients were assigned to a testing cohort (n = 45). LANPC patients were divided into low‐ and high‐risk groups according to their DMFS (P < 0.05). Kaplan–Meier survival analysis was performed to compare the DMFS of different risk groups and subgroup analysis was performed to compare patients treated with CCRT alone and treated with additional chemotherapy to CCRT in different risk groups, respectively.
Statistical Tests
Univariate analysis was performed to identify significant clinical variables. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the model performance.
Results
Our deep‐learning model integrating the deep‐learning signature, node (N) stage (from TNM staging), plasma Epstein–Barr virus (EBV)‐DNA, and treatment regimens yielded an AUC of 0.796 (95% confidence interval CI: 0.729–0.863), 0.795 (95% CI: 0.540–1.000), and 0.808 (95% CI: 0.654–0.962) in the training, internal validation, and external testing cohorts, respectively. Low‐risk patients treated with CCRT alone had longer DMFS than patients treated with additional chemotherapy to CCRT (P < 0.05).
Data Conclusion
The proposed deep‐learning model, based on MRI features and clinical variates, facilitated the prediction of DMFS in LANPC patients.
Level of Evidence
3.
Technical Efficacy Stage
4.
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 present study aimed to identify clinicopathological characteristics of breast cancer liver metastasis (BCLM) as well as to characterize the risk and prognostic factors for the liver metastasis ...(LM) of breast cancer patients with
and relapsed distant metastasis in a Chinese population.
Patients with metastatic breast cancer (MBC) who were hospitalized in the Breast Cancer Center at Chongqing University between January 2011 and December 2019 were included in the present study. Logistic regression analyses were conducted to identify risk factors for the presence of BCLM. Cox proportional hazard regression models were performed to determine the prognostic factors for the survival of BCLM patients. The correlation between LM and overall survival was assessed by the Kaplan-Meier method.
In total, 1,228 eligible MBC patients, including 325 cases (26.5%) with
metastasis (cohort A) and 903 cases (73.5%) with relapsed metastasis (cohort B), were enrolled in the present study. In cohort A and cohort B, 81 (24.9%) and 226 (25.0%) patients had BCLM, respectively. Patients in these two cohorts had different clinicopathological features. Logistic regression analysis identified that the human epidermal growth factor receptor 2 (HER2) status in cohort A as well as the HER2 status and invasive ductal carcinoma histology in cohort B were risk factors for BCLM. The median OS of patients with LM was inferior to that of non-LM patients (17.1
37.7 months,
= 0.0004 and 47.6
84.0 months,
< 0.0001, respectively). Cox analysis identified that the primary T stage, Ki67 level, and breast surgery history were independent prognostic factors for cohorts A and B, respectively.
and relapsed MBC patients have different risk and prognostic factors for LM. Patients with BCLM have an unfavorable prognosis.
Abstract Background and purpose Radiomics provides opportunities to quantify the tumor phenotype non-invasively by applying a large number of quantitative imaging features. This study evaluates ...computed-tomography (CT) radiomic features for their capability to predict distant metastasis (DM) for lung adenocarcinoma patients. Material and methods We included two datasets: 98 patients for discovery and 84 for validation. The phenotype of the primary tumor was quantified on pre-treatment CT-scans using 635 radiomic features. Univariate and multivariate analysis was performed to evaluate radiomics performance using the concordance index (CI). Results Thirty-five radiomic features were found to be prognostic (CI > 0.60, FDR < 5%) for DM and twelve for survival. It is noteworthy that tumor volume was only moderately prognostic for DM (CI = 0.55, p -value = 2.77 × 10−5 ) in the discovery cohort. A radiomic-signature had strong power for predicting DM in the independent validation dataset (CI = 0.61, p -value = 1.79 × 10−17 ). Adding this radiomic-signature to a clinical model resulted in a significant improvement of predicting DM in the validation dataset ( p -value = 1.56 × 10−11 ). Conclusions Although only basic metrics are routinely quantified, this study shows that radiomic features capturing detailed information of the tumor phenotype can be used as a prognostic biomarker for clinically-relevant factors such as DM. Moreover, the radiomic-signature provided additional information to clinical data.
Breast cancer is one of the most commonly diagnosed cancers, and the fourth leading cause of cancer deaths in females worldwide. Sarcopenia is related to adverse clinical outcomes in patients with ...malignancies. Muscle index is a key parameter in evaluating sarcopenia. However, there is no data investigating the association between muscle index and distant metastasis in breast cancer. The aim of this study was to explore whether muscle index can effectively predict distant metastasis and death outcomes in breast cancer patients.
The clinical data of 493 breast cancer patients at the Harbin Medical University Cancer Hospital between January 2014 and December 2015 were retrospectively analyzed. Quantitative measurements of pectoralis muscle area and skeletal muscle area were performed at the level of the fourth thoracic vertebra (T4) and the eleventh thoracic vertebra (T11) of the chest computed tomography image, respectively. The pectoralis muscle index (PMI) and skeletal muscle index (SMI) were assessed by the normalized muscle area (area/the square of height). Survival analysis was performed using the log-rank test and Cox proportional hazards regression analysis.
The patients with metastases had lower PMI at T4 level (PMI/T4) and SMI at T11 level (SMI/T11) compared with the patients without metastases. Moreover, there were significant correlations between PMI/T4 and lymphovascular invasion, Ki67 expression, multifocal disease, and molecular subtype. In addition, multivariate analysis revealed that PMI/T4, not SMI/T11, was an independent prognostic factor for distant metastasis-free survival (DMFS) and overall survival (OS) in breast cancer patients.
Low PMI/T4 is associated with worse DMFS and OS in breast cancer patients. Future prospective studies are needed.
This study aimed to explore a visual model for predicting the prognosis of patients with parathyroid carcinoma (PC) and analyze related biochemistries in different groups of stage.
The training ...dataset of 342 patients with PC was obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and the validation dataset included 59 patients from The First Affiliated Hospital of Zhengzhou University. Univariate and multivariate Cox regression analyses were performed to evaluate significant independent prognostic factors. Based on those factors, nomograms and Web-based probability calculators were constructed to evaluate the overall survival (OS) and the cancer-specific survival (CSS) at 3, 5, and 8 years. The concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram in the training set and validation set. Moreover, biochemistries from the validation set were retrospectively analyzed in different groups of stage by Kruskal-Wallis test.
Age, marital status, tumor size, stage, lymph node status, and radiation were identified as prognostic factors of OS. In contrast, only tumor size and stage were predictive for CSS. The nomogram was developed based on these independent factors. The C-index, ROC curve, calibration curve, and DCA of the nomogram in both training and validation sets showed that the nomogram had good predictive value, stability, and clinical benefit in predicting 3-, 5-, and 8-year OS and CSS in PC patients. Among the 59 PC patients from our hospital, lower albumin (ALB) levels and higher postoperative parathyroid hormone (PTH) levels were found in patients with distant metastasis (Distant vs. Regional ALB levels:
= 0.037; Distant vs. Local ALB levels:
= 0.046; Distant vs. Regional postoperative PTH levels:
= 0.002; Distant vs. Local postoperative PTH:
= 0.002).
The established nomogram application can provide accurate prognostics for patients with PC in the Chinese population, but it must be validated on prospectively collected real-world data.
The tumor microenvironment (TME) is being increasingly recognized as a key factor in multiple stages of disease progression, particularly local resistance, immune-escaping, and distant metastasis, ...thereby substantially impacting the future development of frontline interventions in clinical oncology. An appropriate understanding of the TME promotes evaluation and selection of candidate agents to control malignancies at both the primary sites as well as the metastatic settings. This review presents a timely outline of research advances in TME biology and highlights the prospect of targeting the TME as a critical strategy to overcome acquired resistance, prevent metastasis, and improve therapeutic efficacy. As benign cells in TME niches actively modulate response of cancer cells to a broad range of standard chemotherapies and targeted agents, cancer-oriented therapeutics should be combined with TME-targeting treatments to achieve optimal clinical outcomes. Overall, a body of updated information is delivered to summarize recently emerging and rapidly progressing aspects of TME studies, and to provide a significant guideline for prospective development of personalized medicine, with the long term aim of providing a cure for cancer patients.
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.
We report a case of squamous cell carcinoma of the rectosigmoid colon. A 77-year-old woman found to have a liver tumor during a follow-up MRI examination for a pancreatic nodule. Colonoscopy ...performed subsequently revealed a tumor in the rectosigmoid colon, which was histopathologically diagnosed as a squamous cell carcinoma. CT and MRI revealed invasion of the uterus by the rectosigmoid tumor and a metastasis in the left ovary; based on the findings, the patient was diagnosed as having rectosigmoid colon cancer with multiple organ metastases. We performed rectosigmoid colon resection, also resecting the liver and left ovarian metastases. Histopathological examination of these tumors showed squamous cell carcinoma, and the clinical stage was categorized as Stage IVb. Cancer cells were detected by lavage cytology during the operation; therefore, curative surgery was not possible. The patient was discharged 27 days after the surgery. Although she subsequently received chemotherapy, she died 8 months postoperatively due to cancerous peritonitis. SCC of the colon and rectum are rarely reported. The prognosis is not always unsatisfactory and few reports on some established therapies for this type of malignancy have been presented so far.
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