Evidence map›Paper›PMID 38187111›Full record

ReviewEuropean journal of breast health2024

Factors Affecting Pathological Complete Response in Locally Advanced Breast Cancer Cases Receiving Neoadjuvant Therapy: A Comprehensive Literature Review.

Munaser Alamoodi

Abstract readReview
In one paragraph

Review in European journal of breast health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Munaser AlamoodiDepartment of Surgery, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID https://orcid.org/0000-0001-8218-885X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Determining pathological complete response (pCR) could be an important step in planning individual treatment, hence improving the prognosis in terms of survival. Achieving breast pCR not only improves survival but is also linked to a disease-free axilla, therefore increasing the likelihood of avoiding axillary surgery safely. The current trend in de-escalating axillary management surgically or in applying radiotherapy to the axilla is dependent primarily on breast cancer (BC) patients achieving pCR. Studies have demonstrated that certain characteristics can predict pCR, even though it is still difficult to identify these elements. A review of the literature was carried out to determine these factors and their clinical applications. A search was carried out in the MEDLINE database using PubMed, Google Scholar, and EMBASE. This yielded 1368 studies, of which 60 satisfied the criteria. The studies were categorized according to the subject they dealt with. These parameters included age, race, subtypes, clinicopathological, immunological, imaging, obesity, Ki-67 status, vitamin D, and genetics. These factors, in combination, can be used for specific subtypes to individualize treatment and monitor response to therapy. The predictors of pCR are diverse and should be utilized to personalize patient treatment, ultimately inducing the best outcomes. These determinants can also be employed for monitoring responses to neoadjuvant therapy, thereby adjusting treatment. The development of standardized markers for the diversity of BC subtypes still needs additional future research. These factors must be applied in concert in order to provide optimal results.

Indexed as

early breast cancerneoadjuvant therapyPathological complete responsepCR biomarkers

Identifiers

PMID38187111
PMCPMC10765459

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.