Evidence map›Paper›PMID 42782881›Full record

ArticleCurrent oncology (Toronto, Ont.)2026

Pretreatment Ki67-to-ADC Ratio Predicts Prognosis in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy: A Retrospective Cohort Study.

Jun Fan, Lin Lin, Yang Tao, Yanjia Fan, Yudi Jin, Fajin Lv

Abstract read
In one paragraph

Article in Current oncology (Toronto, Ont.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jun FanDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Lin LinDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.ORCID 0009-0002-8221-4055
Yang TaoDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Yanjia FanDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Yudi JinDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Fajin LvDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.ORCID 0000-0002-6484-9738

Funding

the First Affiliated Hospital of Chongqing Medical University CYYY-BSYJSKYCXXM202412
6 · The paper itself

Abstract

(1) Background: Neoadjuvant chemotherapy (NAC) is important for breast cancer, but prognosis varies widely. Ki67 and apparent diffusion coefficient (ADC) reflect proliferation and cellularity, respectively. This study evaluated the prognostic value of the Ki67/ADC ratio (KA) and post-treatment ADC change (δADC) in breast cancer patients receiving NAC, and developed a survival prediction model incorporating these indicators. (2) Methods: Two cohorts of breast cancer patients treated with NAC were collected. Pre- and post-treatment breast MRI with diffusion-weighted imaging were obtained; ADC values were measured by two blinded radiologists. KA was calculated as pre-treatment Ki67 divided by pre-treatment ADC, and δADC as post-ADC minus pre-ADC. Disease-free survival (DFS) was the primary outcome. Cox regression and a predictive Cox model were used. (3) Results: A total of 419 patients were analyzed. Both KA and δADC were associated with survival. In multivariable analysis, KA remained an independent prognostic factor (HR 0.40, 95% CI 0.19-0.84,

Indexed as

Breast NeoplasmsKi-67 AntigenNeoadjuvant TherapyAdultAgedDiffusion Magnetic Resonance ImagingFemaleHumansMiddle AgedPrognosisRetrospective StudiesKi-67 AntigenADCbreast cancerKi67neoadjuvant chemotherapypredictive modelprognosisδADC

Identifiers

PMID42782881
PMCPMC13605751

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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.