ArticleIrish journal of medical science2023
Breast cancer risk coordinators: Artificial intelligence-based density measurement and Mullerian-inhibiting substance.
Article in Irish journal of medical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDue to its increasing prevalence, breast cancer has become a serious public health problem. In addition to the models used to identify individuals at risk, the search for fast and accurate tools has continued for years.
aimsIn our study, we aimed to examine the correlation of mammographic density measurement and serum Mullerian-inhibiting substance (MIS) levels with an effective model such as Gail.
methodsOf the women whose serum MIS levels were measured in the last 1 year, 214 participants who applied for routine breast examination were included in the study. The age range was between 40 and 60. Exclusion criteria were determined as pathological mammographic findings, active breast symptom, and thoracic radiotherapy history. Mammographic density measurement (PD) was performed with the artificial intelligence-based Deep-LIBRA software. The relationship of these two parameters with the lifetime risk of developing breast cancer was examined.
resultsThe correlation between PD and GRP was remarkable (p < 0.01 cc:0.35). A positive correlation was observed between serum MIS levels and increased breast cancer, but it was not possible to prove this statistically (p = 0.056). It was thought that this situation was caused by perimenopausal patients. Because when the menopause group was excluded, the correlation between MIS levels and GRP decreased (p = 0.12 cc:0.17).
conclusionsPD measurement can be considered as a promising method for the determination of individuals at risk for breast cancer in a large group of patients, but we think that serum MIS levels are not suitable for risk assessment in perimenopausal patients.
Indexed as
Identifiers
36229588What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.