Evidence map›Paper›PMID 34888231›Full record

ArticleFrontiers in oncology2021

Predicting Pathological Complete Response After Neoadjuvant Chemotherapy in Advanced Breast Cancer by Ultrasound and Clinicopathological Features Using a Nomogram.

Hao Cui, Dantong Zhao, Peng Han, Xudong Zhang, Wei Fan, Xiaoxuan Zuo, Panting Wang, Nana Hu, Hanqing Kong, Fuhui Peng and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.0field-weighted citation impact, top 29% of its field
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

15 citing papers in PubMed, 14 citations in OpenAlex.

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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

13 authors at 3 institutions in 1 country.

Hao CuiDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Dantong ZhaoDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Peng HanDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xudong ZhangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Wei FanDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xiaoxuan ZuoDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Panting WangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Nana HuDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Hanqing KongDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Fuhui PengDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Ying WangDepartment of General Surgery, The Second Affiliated Hospital of Hebei Medical University, Shijiazhuang, China.
Jiawei TianDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Lei ZhangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Harbin Medical University · CNSecond Affiliated Hospital of Harbin Medical University · CNSecond Hospital of Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsPrediction of pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer is critical for surgical planning and evaluation of NAC efficacy. The purpose of this project was to assess the efficiency of a novel nomogram based on ultrasound and clinicopathological features for predicting pCR after NAC.

methodsThis retrospective study included 282 patients with advanced breast cancer treated with NAC from two centers. Patients received breast ultrasound before NAC and after two cycles of NAC; and the ultrasound, clinicopathological features and feature changes after two cycles of NAC were recorded. A multivariate logistic regression model was combined with bootstrapping screened for informative features associated with pCR. Then, we constructed two nomograms: an initial-baseline nomogram and a two-cycle response nomogram. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were analyzed. The C-index was used to evaluate predictive accuracy.

resultsSixty (60/282, 21.28%) patients achieved pCR. Triple-negative breast cancer (TNBC) and HER2-amplified types were more likely to obtain pCR. Size shrinkage, posterior acoustic pattern, and elasticity score were identified as independent factors by multivariate logistic regression. In the validation cohort, the two-cycle response nomogram showed better discrimination than the initial-baseline nomogram, with the C-index reaching 0.79. The sensitivity, specificity, and NPV of the two-cycle response nomogram were 0.77, 0.77, and 0.92, respectively.

conclusionThe two-cycle response nomogram exhibited satisfactory efficiency, which means that the nomogram was a reliable method to predict pCR after NAC. Size shrinkage after two cycles of NAC was an important in dependent factor in predicting pCR.

Indexed as

breast cancerneoadjuvant chemotherapynomogrampathological complete responseultrasound

Identifiers

PMID34888231
PMCPMC8650158
OpenAlexW3217119353

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Registered trials

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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.