Evidence map›Paper›PMID 38813284›Full record

ReviewCureus2024

A Comprehensive Review of Taxane Treatment in Breast Cancer: Clinical Perspectives and Toxicity Profiles.

Ashish Jivani, Raju K Shinde

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Predicting taxane-induced peripheral neuropathy by nailfold capillaroscopy: The CAPNEU pilot study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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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

2 authors.

Ashish JivaniGeneral Surgery, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Raju K ShindeGeneral Surgery, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Taxanes, such as paclitaxel and docetaxel, have transformed the landscape of breast cancer treatment, playing pivotal roles in chemotherapy protocols for both early-stage and advanced/metastatic diseases. While these agents have demonstrated remarkable efficacy in enhancing patient outcomes, they are also linked to a range of adverse effects that can impact treatment tolerability and quality of life. This comprehensive review offers an in-depth exploration of taxane therapy in breast cancer, with a focus on clinical perspectives and toxicity profiles. We delineate the mechanisms of action of taxanes, their clinical effectiveness across various breast cancer subtypes, and the prevalent adverse effects encountered in clinical practice. Moreover, we deliberate on strategies for mitigating taxane-associated toxicity and optimizing treatment selection and sequencing based on individual patient characteristics and therapeutic objectives. Finally, we underscore areas for future research and advancement, encompassing the development of novel formulations, the identification of predictive biomarkers for treatment response, and the exploration of combination therapies to bolster therapeutic outcomes. By amalgamating existing evidence and clinical insights, this review aims to apprise clinicians and researchers of the current status of taxane treatment in breast cancer and steer endeavors toward further enhancing patient care and outcomes.

Indexed as

breast cancerchemotherapyclinical perspectivestaxanestoxicitytreatment optimization

Identifiers

PMID38813284
PMCPMC11135142

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.