ReviewHolistic integrative oncology2022
An appropriate treatment interval does not affect the prognosis of patients with breast Cancer.
Review in Holistic integrative oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Risk Factors Associated with Delayed Breast Cancer Diagnoses: What Are We Missing?Journal of general internal medicine · 2026Article
- Burden and temporal trends of female-specific cancers in China: A systematic analysis of the 2023 global burden of disease study.PloS one · 2026Article
- Article
- Prognostic Significance of Delays in Initiation of Adjuvant Trastuzumab-Based Therapy in Patients with HER2-Positive Breast Cancer.Biomedicines · 2025Article
- Breast cancer: pathogenesis and treatments.Signal transduction and targeted therapy · 2025Review
- The negative impact of the COVID-19 pandemic on breast cancer care in Brazil: a time series study in regions with different human development indices.BMC public health · 2024Article
- Outcomes of a Multidisciplinary Team in the Management of Patients with Early-Stage Breast Cancer Undergoing Neoadjuvant Chemotherapy at a Community Cancer Center.Current oncology (Toronto, Ont.) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Major public health emergencies may lead to delays or alterations in the treatment of patients with breast cancer at each stage of diagnosis and treatment. How much do these delays and treatment changes affect treatment outcomes in patients with breast cancer? Methods: This review summarized relevant research in the past three decades and identified the effect of delayed treatment on the prognosis of patients with breast cancer in terms of seeking medical treatment, neoadjuvant treatment, surgery, postoperative chemotherapy, radiotherapy, and targeted therapies. Results: Delay in seeking medical help for ≥12 weeks affected the prognosis. Surgical treatment within 4 weeks of diagnosis did not affect patient prognosis. Starting neoadjuvant chemotherapy within 8 weeks after diagnosis, receiving surgical treatment at 8 weeks or less after the completion of neoadjuvant chemotherapy, and receiving radiotherapy 8 weeks after surgery did not affect patient prognosis. Delayed chemotherapy did not increase the risk of relapse in patients with luminal A breast cancer. Every 4 weeks of delay in the start of postoperative chemotherapy in patients with luminal B, triple-negative, or HER2-positive breast cancer treated with trastuzumab will adversely affect the prognosis. Targeted treatment delays in patients with HER2-positive breast cancer should not exceed 60 days after surgery or 4 months after diagnosis. Radiotherapy within 8 weeks after surgery did not increase the risk of recurrence in patients with early breast cancer who were not undergoing adjuvant chemotherapy. Conclusion: Different treatments have different time sensitivities, and the careful evaluation and management of these delays will be helpful in minimizing the negative effects on patients.
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Registered trials
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.