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Cancer Management and Research 2021Mucinous adenocarcinoma (MA) is a subtype of colorectal cancer (CRC) associated with a higher incidence of local extension and worse survival compared to non-mucinous...
BACKGROUND
Mucinous adenocarcinoma (MA) is a subtype of colorectal cancer (CRC) associated with a higher incidence of local extension and worse survival compared to non-mucinous adenocarcinoma, but few studies have investigated surgery-related predictors for recurrence of MA. Therefore, we aimed to elucidate the predictors for local recurrence and remote metastasis of MA after surgery.
PATIENTS AND METHODS
This study retrospectively analyzed 162 patients with mucinous colorectal adenocarcinoma (MAC) after radical resection. Analysis variables included demographics, clinical indicators, pathologic stage, surgical procedure, adjuvant therapy, and recurrence. Univariate and multivariate analyses were performed to investigate the risk factors for local and distant tumor relapse.
RESULTS
A total of 162 patients (86 male) with a mean age of 58.26 years were included; 70.37% of patients had colonic tumors, and 29.63% had rectal tumors. The 5-year disease-free survival (DFS) rates for these patients were as follows: 100% for TNM stage I, 71.2% for stage II, and 47.8% for stage III. Five-year DFS rates of MAC, colonic and rectal MA were 62.0%, 65.8%, and 51.7%, respectively. Local recurrence occurred in 38 patients and distant metastasis in 33 patients. In univariate analysis, predictors for local recurrence of MAC were intraoperative blood loss, intraoperative transfusion, and N2 stage; and predictors for distant metastasis were male sex, CA199, CEA, intraoperative blood loss, T4 stage, and N2 stage. In multivariate analysis, predictors for local recurrence of MAC were intraoperative transfusion (=0.04, =4.175) and N2 stage (=0.000, =5.291), and predictors for distant metastasis were male sex (=0.049, =2.410), CA199 (=0.02, =1.003), and T4 stage (=0.007, =4.006).
CONCLUSION
Intraoperative transfusion and N2 stage were significant predictors for local recurrence. Male sex, CA199, and T4 stage were significant predictors for distant metastasis. Knowledge of the risk factors for postoperative recurrence provides a basis for logical approaches to treatment and follow-up of MAC.
PubMed: 34168497
DOI: 10.2147/CMAR.S313627 -
European Journal of Medical Research Dec 2022Distant metastasis, which occurs at a rate of 25% in patients with esophageal cancer (EC), has a poor prognosis, with previous studies reporting an overall survival of... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Distant metastasis, which occurs at a rate of 25% in patients with esophageal cancer (EC), has a poor prognosis, with previous studies reporting an overall survival of only 3-10 months. However, few studies have been conducted to predict distant metastasis in EC, owing to a dearth of reliable biomarkers. The purpose of this study was to develop and validate an accurate model for predicting distant metastasis in patients with EC.
METHODS
A total of 299 EC patients were enrolled and randomly assigned to a training cohort (n = 207) and a validation cohort (n = 92). Logistic univariate and multivariate regression analyses were used to identify clinical independent predictors and create a clinical nomogram. Radiomic features were extracted from contrast-enhanced computed tomography (CT) images taken prior to treatment, and least absolute shrinkage and selection operator (Lasso) regression was used to screen the associated features, which were then used to develop a radiomic signature. Based on the screened features, four machine learning algorithms were used to build radiomics models. The joint nomogram with radiomic signature and clinically independent risk factors was developed using the logical regression algorithm. All models were validated and compared by discrimination, calibration, reclassification, and clinical benefit.
RESULTS
Multivariable analyses revealed that age, N stage, and degree of pathological differentiation were independent predictors of distant metastasis, and a clinical nomogram incorporating these factors was established. A radiomic signature was developed by a set of sixteen features chosen from 851 radiomic features. The joint nomogram incorporating clinical factors and radiomic signature performed better [AUC(95% CI) 0.827(0.742-0.912)] than the clinical nomogram [AUC(95% CI) 0.731(0.626-0.836)] and radiomics predictive models [AUC(95% CI) 0.754(0.652-0.855), LR algorithms]. Calibration and decision curve analyses revealed that the radiomics-clinical nomogram outperformed the other models. In comparison with the clinical nomogram, the joint nomogram's NRI was 0.114 (95% CI 0.075-0.345), and its IDI was 0.071 (95% CI 0.030-0.112), P = 0.001.
CONCLUSIONS
We developed and validated the first radiomics-clinical nomogram for distant metastasis in EC which may aid clinicians in identifying patients at high risk of distant metastasis.
Topics: Humans; Esophageal Neoplasms; Algorithms; Tomography, X-Ray Computed; Ethnicity; Multivariate Analysis
PubMed: 36463269
DOI: 10.1186/s40001-022-00877-8 -
BMC Cancer Mar 2023Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the...
BACKGROUND
Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis.
METHODS
We retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data.
RESULTS
Three clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients.
CONCLUSION
Our study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.
Topics: Humans; Female; Breast Neoplasms; Retrospective Studies; Artificial Intelligence; Nomograms; Bone Neoplasms
PubMed: 36918809
DOI: 10.1186/s12885-023-10704-w -
Journal of Clinical Medicine Nov 2021Cutaneous melanoma is the most dangerous skin cancer, with high death rates in advanced stages. To assess the impact of each treatment on patient outcomes, most studies... (Review)
Review
Cutaneous melanoma is the most dangerous skin cancer, with high death rates in advanced stages. To assess the impact of each treatment on patient outcomes, most studies use relapse-free survival (RFS) as a primary endpoint and distant metastasis-free survival (DMFS) as a secondary endpoint. The aim of this narrative review of the main adjuvant studies for resected stage III/IV melanoma, with a specific focus on DMFS, is to evaluate DMFS trends and their potential association with RFS, identify which treatments are possibly associated with better outcomes in terms of DMFS and their potential predictive factors, and discuss DMFS trends in terms of patient management in daily practice. We outline the impact of each available treatment option on DMFS and RFS according to the years of follow-up and compare data from different studies. Overall, the trends of DMFS closely follow those of RFS, with most patients relapsing at visceral rather than regional sites. As it captures the burden of patients who develop distant relapse, DMFS could be considered a primary endpoint, in addition to RFS, in adjuvant trials, identifying patients whose relapse is associated with a worse prognosis and who may need further systemic treatment.
PubMed: 34884176
DOI: 10.3390/jcm10235475 -
BMC Urology Dec 2022Urothelial carcinoma is the most common type of bladder cancer worldwide and it has a poor prognosis for patients with distant metastasis. Nomograms are frequently used...
Constructing and validating nomograms to predict risk and prognostic factors of distant metastasis in urothelial bladder cancer patients: a population-based retrospective study.
BACKGROUND
Urothelial carcinoma is the most common type of bladder cancer worldwide and it has a poor prognosis for patients with distant metastasis. Nomograms are frequently used in clinical research, but no research has evaluated the diagnostic and prognostic factors of distant metastasis in urothelial bladder cancer (UBC).
METHODS
The Surveillance, Epidemiology, and End Results database was used to analyze all patients diagnosed with UBC between 2000 and 2017. Lasso regression was used to identify the potential risk predictive factors for distant metastasis in UBC. Univariate and multivariate Cox proportional hazard regression analyses were performed to determine independent prognostic factors for distant metastasis urothelial bladder cancer (DMUBC). Subsequently, two nomograms were constructed based on the above models. The receiver operating characteristic (ROC), and calibration curves were performed to evaluate the two nomograms.
RESULTS
The study included 73,264 patients with UBC, with 2,129 (2.9%) having distant metastasis at the time of diagnosis. In the diagnostic model, tumor size, histologic type, and stage N and T were all important risk predictive factors for distant metastasis of UBC. In the prognostic model, age, tumor size, surgery, and chemotherapy were independent factors affecting the prognosis of DMUBC. DCA, ROC, calibration, and Kaplan-Meier (K-M) survival curves reveal that the two nomograms can effectively predict the diagnosis and prognosis of DMUBC.
CONCLUSION
The developed nomograms are practical methods for predicting the occurrence risk and prognosis of distant metastasis urothelial bladder cancer patients, which may benefit the clinical decision-making process.
Topics: Humans; Carcinoma, Transitional Cell; Urinary Bladder Neoplasms; Nomograms; Retrospective Studies; Prognosis; Risk Factors; Neoplasm Staging
PubMed: 36575440
DOI: 10.1186/s12894-022-01166-6 -
Cancer Management and Research 2022This study aimed to summarize the clinical characteristics, treatment, and outcomes of distant metastatic retinoblastoma with event-free survival.
AIM
This study aimed to summarize the clinical characteristics, treatment, and outcomes of distant metastatic retinoblastoma with event-free survival.
DESIGN
Retrospective interventional case series.
METHODS
We screened patients with retinoblastoma who survived without events after the comprehensive treatment of distant metastases from June 2015 to February 2021 and collected information regarding their basic characteristics, diagnosis, and treatment. All patients received systemic intravenous chemotherapy. Other treatments included surgical treatment, radiotherapy, intrathecal chemotherapy, and autologous stem cell transplantation.
RESULTS
Among 780 hospitalized patients with retinoblastoma in the pediatric ward, a total of 94 patients with retinoblastoma were diagnosed with distant metastases, and 16 patients with distant metastatic retinoblastoma who survived more than 6 months without events were screened, including eight male and eight female patients. The median age of onset was 29 (range, 11-120) months. Among the 16 patients, central nervous system metastasis (8/16), bone metastasis (8/16), bone marrow infiltration (4/16), lymph node metastasis (4/16), and parotid gland metastasis (3/16) were presented. All patients received treatment for more than 6 months, completed their regimen by February 2021, and survived without events. The median survival time after the onset of retinoblastoma was 50.5 (range, 23-102) months, the median survival time after metastasis was 43.5 (range, 16-71) months, and the median event-free survival was 29.0 (range, 6-59) months.
CONCLUSION
Metastatic retinoblastoma may benefit from comprehensive treatments including systemic intravenous chemotherapy and hematopoietic stem cell transplantation. However, recurrence after treatment still needs attention, and patients in complete remission still need long-term follow-up.
PubMed: 35115833
DOI: 10.2147/CMAR.S349035 -
IEEE Journal of Biomedical and Health... Oct 2021Medical image processing is one of the most important topics in the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-art...
Medical image processing is one of the most important topics in the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-art performances on medical imaging tasks. In this paper, we propose a novel transfer learning framework for medical image classification. Moreover, we apply our method COVID-19 diagnosis with lung Computed Tomography (CT) images. However, well-labeled training data sets cannot be easily accessed due to the disease's novelty and privacy policies. The proposed method has two components: reduced-size Unet Segmentation model and Distant Feature Fusion (DFF) classification model. This study is related to a not well-investigated but important transfer learning problem, termed Distant Domain Transfer Learning (DDTL). In this study, we develop a DDTL model for COVID-19 diagnosis using unlabeled Office-31, Caltech-256, and chest X-ray image data sets as the source data, and a small set of labeled COVID-19 lung CT as the target data. The main contributions of this study are: 1) the proposed method benefits from unlabeled data in distant domains which can be easily accessed, 2) it can effectively handle the distribution shift between the training data and the testing data, 3) it has achieved 96% classification accuracy, which is 13% higher classification accuracy than "non-transfer" algorithms, and 8% higher than existing transfer and distant transfer algorithms.
Topics: COVID-19; Humans; Machine Learning; Tomography, X-Ray Computed
PubMed: 33449887
DOI: 10.1109/JBHI.2021.3051470 -
Cancer Epidemiology, Biomarkers &... Jun 2022This study examines the association between Medicaid enrollment, including through the National Breast and Cervical Cancer Early Detection Program (NBCCEDP), and distant...
BACKGROUND
This study examines the association between Medicaid enrollment, including through the National Breast and Cervical Cancer Early Detection Program (NBCCEDP), and distant stage for three screening-amenable cancers: breast, cervical, and colorectal.
METHODS
We use the Surveillance, Epidemiology, and End Results Cancer Registry linked with Medicaid enrollment data to compare patients who were Medicaid insured with patients who were not Medicaid insured. We estimate the likelihood of distant stage at diagnosis using logistic regression.
RESULTS
Medicaid enrollment following diagnosis was associated with the highest likelihood of distant stage. Medicaid enrollment through NBCCEDP did not mitigate the likelihood of distant stage disease relative to Medicaid enrollment prior to diagnosis. Non-Hispanic Black patients had a greater likelihood of distant stage breast and colorectal cancer. Residing in higher socioeconomic areas was associated with a lower likelihood of distant stage breast cancer.
CONCLUSIONS
Medicaid enrollment prior to diagnosis is associated with a lower likelihood of distant stage in screen amenable cancers but does not fully ameliorate disparities.
IMPACT
Our study highlights the importance of health insurance coverage prior to diagnosis and demonstrates that while targeted programs such as the NBCCEDP provide critical access to screening, they are not a substitute for comprehensive insurance coverage.
Topics: Breast Neoplasms; Early Detection of Cancer; Female; Humans; Insurance Coverage; Mass Screening; Medicaid; Neoplasm Staging; United States
PubMed: 35322273
DOI: 10.1158/1055-9965.EPI-21-1077 -
The Journal of Thoracic and... Oct 2021The purpose of this study was to recognize clinically meaningful differences in lung transplant outcomes based on local or distant lung procurement. This could identify...
OBJECTIVE
The purpose of this study was to recognize clinically meaningful differences in lung transplant outcomes based on local or distant lung procurement. This could identify if the lung allocation policy change would influence patient outcomes.
METHODS
This single-center retrospective cohort study analyzed adult patients who underwent lung transplant from 2006 to 2017. Donor and recipient data were abstracted from a collaborative, prospective registry shared by our local organ procurement organization, and tertiary medical center. Short-term outcomes, 1-year survival, and hospitalization costs were compared between local and distant lung transplants defined by donor service area.
RESULTS
Of the 722 lung transplants performed, 392 (54%) had local donors and 330 (46%) had distant donors. Donors were similar in age and cause of death. Recipients were significantly different in diagnosis and local recipients had lower median lung allocation scores (local, 37.3 and distant, 44.9; P < .01). Distant lung transplants had longer total ischemic times (local, 231 ± 52 minutes and distant, 313 ± 48 minutes; P < .01). The rate of major complications, length of hospital stay, and 1-year survival were similar between groups. Distant lung transplants were associated with higher median overall cost (local, $183,542 and distant, $229,871; P < .01). Local lung transplants were more likely to be performed during daytime (local, 333 out of 392 [85%] and distant, 291 out of 330 [61%]; P < .01).
CONCLUSIONS
Local lung transplants are associated with shorter ischemic times, lower cost, and greater likelihood of daytime surgery. Short- and intermediate-term outcomes are similar for lung transplants from local and distant donors. The new lung allocation policy, with higher proportion of distant lung transplants, is likely to incur greater costs but provide similar outcomes.
Topics: Adult; Cold Ischemia; Female; Graft Survival; Humans; Lung; Lung Transplantation; Male; Outcome Assessment, Health Care; Policy Making; Postoperative Complications; Registries; Resource Allocation; Retrospective Studies; Tertiary Care Centers; Tissue Donors; Tissue and Organ Procurement; Topography, Medical; Transplants; United States
PubMed: 32977961
DOI: 10.1016/j.jtcvs.2020.07.115 -
Cancer Causes & Control : CCC May 2022Women with hormone receptor (HR)-positive early-stage breast cancer (BC) have five-year survival rates of > 90% but remain at serious risk for developing distant...
Women with hormone receptor (HR)-positive early-stage breast cancer (BC) have five-year survival rates of > 90% but remain at serious risk for developing distant metastases beyond five years from diagnosis. This retrospective cohort study used data from the Surveillance, Epidemiology, and End Results (SEER) registries to examine associations between distant recurrence-free interval (DRFI) and risk of BC-specific mortality following distant relapse. The analysis includes 1,057 women with second primary stage IV BC who were initially diagnosed with AJCC stages I-III HR-positive BC between1990 and 2016. Overall, 65% of women had a preceding DRFI of ≥ 5 years. Five-year BC-specific survival following development of distant recurrence was 52% for women with DRFI ≥ 5 years compared to 31% in women with DRFI of < 5 years. In multivariable analyses, risks of cancer-specific mortality following distant recurrence were lower in women with DRFI of 5 years or more (subdistribution hazard ratio = 0.72, 95% CI 0.58-0.89, p = 0.002). The results of this study may inform patient-clinician discussions surrounding prognosis and treatment selection among HR-positive patients who develop a distant recurrence of disease.
Topics: Breast Neoplasms; Female; Humans; Neoplasm Recurrence, Local; Neoplasms, Second Primary; Prognosis; Proportional Hazards Models; Retrospective Studies
PubMed: 35226243
DOI: 10.1007/s10552-022-01561-2