Results 51 to 60 of about 1,970 (174)

The sensitivity of CEA, CA153 and CK19-2G2 for PBC and MBC.

open access: yes, 2013
(A) CK19-2G2 is superior to CEA and CA153 in stage II and III breast cancer patients and as sensitive as CA153 in MBC patients. The blank bar: CEA; the gray bar: CA153; the black bar: CK19-2G2 (B) The distribution of CK19-2G2 in MBC, PBC and DCIS.
Yanan Kong (384071)   +14 more
core   +1 more source

ვიტამინი D და ფარისებრი ჯირკვლის ჰორმონები პაციენტებში ძუძუს კეთილთვისებიანი სიმსივნის დროს

open access: yes, 2021
The Breast Benign tumor (BBT) is currently considered a significant breast health problem within women of all ages. In the present study, we aimed to investigate the Tumor markers CA125 and CA153,  thyroid hormones free triiodothyronine (FT3), free ...
RUSUDAN VADACHKORIA   +2 more
core   +1 more source

Identification of Flap Endonuclease 1 With Diagnostic and Prognostic Value in Breast Cancer

open access: yesFrontiers in Oncology, 2021
ObjectiveThis study aims to identify the potential value of flap endonuclease 1 (FEN1) as a diagnostic and prognostic marker for breast cancer (BC).MethodsELISA was used to measure serum FEN1 levels and ECLIA for CA153 and CEA levels.
Min Wu   +6 more
doaj   +1 more source

Kupffer Phase Radiomics Signature in Sonazoid Contrast‐Enhanced Ultrasound Predicts Immunohistochemistry Marker Expression in Hepatocellular Carcinoma

open access: yesCancer Medicine, Volume 14, Issue 19, October 2025.
ABSTRACT Purpose Few studies have explored the value of radiomics signatures in predicting immunohistochemical (IHC) staining markers. This study aimed to investigate and validate radiomics models based on the Kupffer phase of Sonazoid contrast‐enhanced intraoperative ultrasonography (S‐CEUS) images for predicting IHC marker expression in ...
Chen Li   +5 more
wiley   +1 more source

Sensitivity, specificity, and areas under the curves for CEA, CA153 and combinations of these markers in nipple discharge with breast cancer.

open access: yes, 2016
Sensitivity, specificity, and areas under the curves for CEA, CA153 and combinations of these markers in nipple discharge with breast cancer.
Yu Mei (847605)   +4 more
core   +1 more source

Prediction of Lung Cancer Metastasis Using Machine Learning Models Based on Clinical Laboratory Data

open access: yesCancer Reports, Volume 8, Issue 10, October 2025.
ABSTRACT Background Lymph node (N) or/and distant metastasis in lung cancer indicates poorer prognosis. While laboratory tests and computed tomography (CT) scans reflect tumor growth and metabolic activity, they usually require combination with other diagnostic methods to effectively assess metastasis, resulting in limited clinical use of these results.
Chao Du   +6 more
wiley   +1 more source

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer

open access: yesCancer Medicine, 2020
Background This study aimed to explore the possibility of serum tumor markers (TMs) combinations in assessing tumor metastasis in patients with lung cancer.
Jiasi Wang   +10 more
doaj   +1 more source

Efficacy, Safety, and Biomarkers of Neoadjuvant Dalpiciclib (CDK4/6 inhibitor) plus Aromatase Inhibitors in Operable HER2‐Negative Luminal B Breast Cancer: A Prospective, Single‐Center, Single‐Arm, Phase II Trial (DANCER)

open access: yesMedComm, Volume 6, Issue 10, October 2025.
DANCER (NCT05640778) was a circulating tumor DNA (ctDNA)‐directed, single‐arm, phase II trial investigating the clinical activity of dalpiciclib combined with aromatase inhibitors as a neoadjuvant regimen for operable human epidermal growth factor receptor 2 (HER2)‐negative luminal B breast cancer. Although a high complete cell cycle arrest (CCCA) rate
Yunxiang Zhou   +21 more
wiley   +1 more source

Application value of the treatment of breast cancer bone metastases with radioactive seed 125I implantation under CT-guidance

open access: yesBMC Medical Imaging, 2022
Background To investigate the application value of the treatment of breast cancer bone metastases with radioactive seed 125I implantation under CT-guidance.
Haiwen Li   +3 more
doaj   +1 more source

Interpretable Machine Learning for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer Using the Baseline Clinical and Pathological Characteristics

open access: yesCancer Medicine, Volume 14, Issue 17, September 2025.
ABSTRACT Background The pathological response to neoadjuvant chemotherapy (NAC) has become a vital prognostic indicator for patients with breast cancer (BC). The newly generated models depended on rather basic imaging and pathology characteristics and did not sufficiently elucidate the importance of the incorporated data.
Shan Fang   +9 more
wiley   +1 more source

Home - About - Disclaimer - Privacy