Evidence map›Paper›PMID 30478672›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2019

Predictive factors for taxane acute pain syndrome determined by ordered logistic regression analysis.

Yuko Kanbayashi, Kouichi Sakaguchi, Katsuhiko Nakatsukasa, Yoshimi Ouchi, Yusuke Tabuchi, Tomoko Yoshioka, Takeshi Ishikawa, Koichi Takayama, Tetsuya Taguchi

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In one paragraph

Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
  6. Dexamethasone dose-dependently prevents taxane-associated acute pain syndrome in breast cancer treatment.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
  7. Risk factor analysis for taxane-associated acute pain syndrome under the dexamethasone prophylaxis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    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

9 authors at 2 institutions in 1 country.

Yuko KanbayashiDepartment of Outpatient Oncology Unit, University Hospital, Kyoto Prefectural University of Medicine, Kyoto, Japan. kanbayashi@gly.oups.ac.jp.ORCID http://orcid.org/0000-0002-4680-5133
Kouichi SakaguchiDepartment of Endocrine and Breast Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Katsuhiko NakatsukasaDepartment of Endocrine and Breast Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Yoshimi OuchiDepartment of Endocrine and Breast Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Yusuke TabuchiDepartment of Outpatient Oncology Unit, University Hospital, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Tomoko YoshiokaDepartment of Outpatient Oncology Unit, University Hospital, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Takeshi IshikawaDepartment of Outpatient Oncology Unit, University Hospital, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Koichi TakayamaDepartment of Pulmonary Medicine and Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Tetsuya TaguchiDepartment of Outpatient Oncology Unit, University Hospital, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Kyoto Prefectural University of Medicine · JPUniversity Hospital Kyoto Prefectural University of Medicine · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This retrospective study was undertaken to identify predictive factors for developing taxane acute pain syndrome (TAPS) and to determine new strategies for improving QoL in patients undergoing chemotherapy. Between November 2010 and May 2018, we enrolled 121 breast cancer patients at our outpatient chemotherapy center who were undergoing chemotherapy with nanoparticle albumin-bound paclitaxel (nab-PTX) every 3 weeks. Variables related to the development of TAPS were extracted from the patients' clinical records and used for regression analysis. The degree of TAPS was classified as grade 0 = not developed; grade 1 = developed but did not require analgesics; grade 2 = developed but alleviated by analgesics such as acetaminophen or non-steroidal anti-inflammatory drugs (NSAIDs); or grade 3 = syndrome developed, causing sleep problems or interfering with daily living activities, but not alleviated by analgesics such as acetaminophen or NSAIDs thus requiring opioids. Multivariate ordered logistic regression analysis was performed to identify predictive factors for the development of TAPS. Significant factors identified for the development of TAPS included dose of nab-PTX (odds ratio (OR) = 11.717, 95% confidence interval (CI) = 11.6161-11.8182; P = 0.0421) and the administration of dexamethasone for up to 3 days (OR = 0.133, 95% CI = 0.0235-0.7450; P = 0.0223). In conclusion, a high dose of nab-PTX and the lack of dexamethasone administration for up to 3 days were identified as significant predictors of the development of TAPS.

Indexed as

Acute PainAdultAgedAlbuminsAnalgesicsAnti-Inflammatory Agents, Non-SteroidalBreast NeoplasmsFemaleHumansLogistic ModelsMiddle AgedPaclitaxelPredictive Value of TestsQuality of LifeRetrospective StudiesRisk Factors130-nm albumin-bound paclitaxelAlbuminsAnalgesicsAnti-Inflammatory Agents, Non-SteroidalPaclitaxelDexamethasoneDoseNanoparticle albumin-bound paclitaxelTAPSTaxanes

Identifiers

PMID30478672
OpenAlexW2902991079

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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.