Evidence map›Paper›PMID 36281495›Full record

ArticleCancer medicine2023

Assessing early changes in plasma HER2 levels is useful for predicting therapeutic response in advanced breast cancer: A multicenter, prospective, noninterventional clinical study.

Yi-Kun Kang, Yi-Ran Si, Jie Ju, Zhu-Qing Jia, Nan-Lin Hu, Hao Dong, Xue Wang, Jian Yue, Pei-Di Jiang, Zhao-Liang Li and 4 more

Open access · goldFull text readMulticenter Study
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

14 authors at 4 institutions in 2 countries.

Yi-Kun KangDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Yi-Ran SiDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Jie JuDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Zhu-Qing JiaBeijing Unicare Hospital, Beijing, China.
Nan-Lin HuDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Hao DongQuestgenomics, Nanjing, China.
Xue WangDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Jian YueDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Pei-Di JiangDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Zhao-Liang LiQuestgenomics, Nanjing, China.
Yun-Yun ZhangQuestgenomics, Nanjing, China.
Yan WangGnomegen, San Diego, California, USA.
Bing-He XuDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Peng YuanDepartment of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.ORCID 0000-0002-5968-0368
Chinese Academy of Medical Sciences & Peking Union Medical College · CNMedomics (China) · CNBeijing Hospital · CNGigaGen (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly prediction of treatment response is crucial for the optimal treatment of advanced breast cancer. We aimed to explore whether monitoring early changes in plasma human epidermal growth factor receptor 2 (HER2) levels using digital PCR (dPCR) could predict the treatment response in advanced breast cancer.

methodsThis was a multicenter, prospective, noninterventional clinical study of patients with advanced breast cancer. All enrolled patients underwent blood testing to measure the HER2 levels by digital PCR before treatment initiation and once every 3 weeks during the study. The primary endpoints were

resultsOverall, 85 patients were enrolled between October 9, 2018, and January 23, 2020. dPCR had a specificity of 91.67% (95% CI: 80.61% to 97.43%) for detecting HER2 amplification, and the area under the receiver operating characteristic (ROC) curve was 0.84 (p < 0.01). A clinically relevant specificity threshold of approximately 90%, which was equivalent to a ≥15% decrease in the plasma HER2 ratio at 3 weeks from baseline, showed a positive predictive value of 97.37% (95% CI: 77.11% to 98.65%) in terms of predicting clinical benefit. Patients whose plasma HER2 ratio was reduced by ≥15% had a longer median progression-free survival (PFS) than those whose ratio was reduced by <15% (9.20 months vs. 4.50 months, p < 0.01).

conclusionsEarly changes in the plasma HER2 ratio may predict the treatment response in patients with advanced breast cancer and could facilitate optimal treatment selection.

Indexed as

Breast NeoplasmsBiomarkers, TumorFemaleHumansPredictive Value of TestsProspective StudiesROC CurveBiomarkers, Tumorbreast cancerdigital PCRplasma HER2prediction thresholdtherapy response

Identifiers

PMID36281495
PMCPMC10028130
OpenAlexW4307228131

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read127
identifiers read2
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.