scholarly journals Distant Resolution of Actinic Keratosis following Cryosurgery: An Unusual Phenomenon

2021 ◽  
pp. 289-292
Author(s):  
Karim Saleh
Keyword(s):  
Breast Cancer ◽  
Clinical Practice ◽  
Actinic Keratosis ◽  
Local Reaction ◽  
Primary Tumour ◽  
Systemic Effects ◽  
Immunological Effect ◽  
Unusual Phenomenon

Early after the introduction of cryosurgery to clinical practice, there were reports of metastasis regressing after cryosurgery of a primary tumour, mainly prostate and breast cancer, suggesting a systemic immunological effect to a local reaction. Colleagues within dermatology have occasionally experienced similar systemic effects following cryosurgery. However, published reports of such cases are lacking. In this case, we report a photographed distant resolution of an actinic keratosis (AK) on 68-year-old woman’s arm following cryosurgery of another AK on the same arm.

Patterns of relapse after neoadjuvant chemotherapy in breast cancer: implications for surveillance in clinical practice

2019 ◽  
Vol 177 (1) ◽  
pp. 197-206
Author(s):  
Stephanie Saw ◽  
John Lim ◽  
Swee Ho Lim ◽  
Mabel Wong ◽  
Cindy Lim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Practice ◽  
Neoadjuvant Chemotherapy

scholarly journals How can artificial intelligence models assist PD-L1 expression scoring in breast cancer: results of multi-institutional ring studies

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xinran Wang ◽  
Liang Wang ◽  
Hong Bu ◽  
Ningning Zhang ◽  
Meng Yue ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Clinical Practice ◽  
Subjective Assessment ◽  
Current Guideline ◽  
Scoring Method ◽  
Programmed Death ◽  
Intelligence Models ◽  
Artificial Intelligence Models ◽  
Scoring Accuracy

AbstractProgrammed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, a repeatable and quantifiable PD-L1 IC scoring method of breast cancer is desirable. In this study, we propose a deep learning-based artificial intelligence-assisted (AI-assisted) model for PD-L1 IC scoring. Three rounds of ring studies (RSs) involving 31 pathologists from 10 hospitals were carried out, using the current guideline in the first two rounds (RS1, RS2) and our AI scoring model in the last round (RS3). A total of 109 PD-L1 (Ventana SP142) immunohistochemistry (IHC) stained images were assessed and the role of the AI-assisted model was evaluated. With the assistance of AI, the scoring concordance across pathologists was boosted to excellent in RS3 (0.950, 95% confidence interval (CI): 0.936–0.962) from moderate in RS1 (0.674, 95% CI: 0.614–0.735) and RS2 (0.736, 95% CI: 0.683–0.789). The 2- and 4-category scoring accuracy were improved by 4.2% (0.959, 95% CI: 0.953–0.964) and 13% (0.815, 95% CI: 0.803–0.827) (p < 0.001). The AI results were generally accepted by pathologists with 61% “fully accepted” and 91% “almost accepted”. The proposed AI-assisted method can help pathologists at all levels to improve the PD-L1 assay (SP-142) IC assessment in breast cancer in terms of both accuracy and concordance. The AI tool provides a scheme to standardize the PD-L1 IC scoring in clinical practice.

scholarly journals 5PSQ-163 Incidence of neutropenia and effectiveness of palbociclib in clinical practice in metastatic breast cancer after 4 years of use

2021 ◽  
Author(s):  
JM Vinuesa Hernando ◽  
M Zurera Berjaga ◽  
R Gracia Piquer ◽  
R Fresquet Molina ◽  
P Gómez Rivas ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Clinical Practice ◽  
Metastatic Breast
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