Evidence map›Paper›PMID 38249333›Full record

ArticleTherapeutic advances in medical oncology2024

The impact of the HER2-low status on conditional survival in patients with breast cancer.

Teng Ma, Changgen Liu, Tianyi Ma, Xinyi Sun, Jian Cui, Lulu Wang, Yan Mao, Haibo Wang

Open access · goldAbstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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

8 authors at 1 institution in 1 country.

Teng MaBreast Disease Center, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China.
Changgen LiuBreast Disease Center, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China.
Tianyi MaBreast Disease Center, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China.
Xinyi SunBreast Disease Center, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China.
Jian CuiBreast Disease Center, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China.
Lulu WangDepartment of Cardiovascular Surgery, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China.
Yan MaoBreast Disease Center, Affiliated Hospital of Qingdao University, No. 59 Haier Road, Laoshan District, Qingdao, Shandong Province 266000, China.
Haibo WangBreast Disease Center, Affiliated Hospital of Qingdao University, No. 59 Haier Road, Laoshan District, Qingdao, Shandong Province 266000, China.ORCID https://orcid.org/0000-0002-5585-704X
Qingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: With recent advances in breast cancer (BC) treatment, the disease-free survival (DFS) of patients is increasing and the risk factors for recurrence and metastasis are changing. However, a dynamic approach to assessing the risk of recurrent metastasis in BC is currently lacking. This study aimed to develop a dynamically changing prediction model for recurrent metastases based on conditional survival (CS) analysis. Methods: Clinical and pathological data from patients with BC who underwent surgery at the Affiliated Hospital of Qingdao University between August 2011 and August 2022 were retrospectively analysed. The risk of recurrence and metastasis in patients with varying survival rates was calculated using CS analysis, and a risk prediction model was constructed. Results: A total of 4244 patients were included in this study, with a median follow-up of 83.16 ± 31.59 months. Our findings suggested that the real-time DFS of patients increased over time, and the likelihood of DFS after surgery correlated with the number of years of prior survival. We explored different risk factors for recurrent metastasis in baseline patients, 3-year, and 5-year disease-free survivors, and found that low HER2 was a risk factor for subsequent recurrence in patients with 5-year DFS. Based on this, conditional nomograms were developed. The nomograms showed good predictive ability for recurrence and metastasis in patients with BC. Conclusion: Our study showed that the longer patients with BC remained disease-free, the greater their chances of remaining disease-free again. Predictive models for recurrence and metastasis risk based on CS analysis can help improve the confidence of patients fighting cancer and help doctors personalise treatment and follow-up plans.

Indexed as

breast cancerconditional survivaldisease-free survivalHER2nomograms

Identifiers

PMID38249333
PMCPMC10799581
OpenAlexW4391053803

What OpenQuestion holds

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LicenceCC BY-NC
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.