Evidence map›Paper›PMID 27274398›Full record

ArticleJournal of pharmaceutical health care and sciences2016

Preliminary study for predicting better methotrexate efficacy in Japanese patients with rheumatoid arthritis.

Masayuki Hashiguchi, Tomomi Tsuru, Kumika Miyawaki, Midori Suzaki, Jun Hakamata, Mikiko Shimizu, Shin Irie, Mayumi Mochizuki

Open access · goldAbstract read
In one paragraph

Article in Journal of pharmaceutical health care and sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 3 pooled it
1.5field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 3 syntheses or guidelines pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Genetic markers in methotrexate treatments.The pharmacogenomics journal · 2018
    Pooled it
  4. 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

8 authors at 1 institution in 1 country.

Masayuki HashiguchiDivision for Evaluation and Analysis of Drug Information, Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512 Japan.
Tomomi TsuruPS Clinic, LTA Clinical Pharmacology Center, 6-18 Tenyacho, Hakata-ku, Fukuoka, 812-0025 Japan.
Kumika MiyawakiDivision for Evaluation and Analysis of Drug Information, Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512 Japan.
Midori SuzakiPS Clinic, LTA Clinical Pharmacology Center, 6-18 Tenyacho, Hakata-ku, Fukuoka, 812-0025 Japan.
Jun HakamataDivision for Evaluation and Analysis of Drug Information, Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512 Japan.
Mikiko ShimizuDepartment of Hygienic Chemistry, Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512 Japan.
Shin IrieLTA Clinical Pharmacology Center, 6-18 Tenyacho, Hakata-ku, Fukuoka, 812-0025 Japan.
Mayumi MochizukiDivision for Evaluation and Analysis of Drug Information, Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512 Japan.
Keio University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRheumatoid arthritis (RA) is a chronic autoimmune disease characterized by systemic inflammatory status, joint destruction, disability, and pain. Methotrexate (MTX) has been confirmed to reduce disease activity and delay or stabilize the development of bone erosions. However, major drawbacks are that patients show great interindividual variability in response to MTX and the unpredictable occurrence of side effects. A strategy for personalized MTX treatment to predict its efficacy and toxicity has not yet been determined. To establish personalized MTX therapy in Japanese patients with rheumatoid arthritis, we performed a preliminary study for predicting better methotrexate efficacy including single-nucleotide polymorphisms (SNPs) for MTX-related transporters/enzymes.

methodsDisease control status (good or poor) was judged by the number of Disease Activity Scores (DAS28) of <2 for 6-12 months. The response index R was calculated by the improved area under the curve (AUC) of the DAS28 score for 0-3 or 0-6 months by dividing the cumulative dose of MTX during 0-3 or 0-6 months, respectively. Genotyping of alleles of RFC1 80G > A, RFC1 -43 T > C, FPGS 1994G > A, GGH 401C > T, MTHFR 1298A > C, and TYMS 3'-UTR (-6/+6) was performed using the real-time PCR system.

resultsSeven of 21 patients were judged as good responders in terms of disease control, and the remainder as poor responders. For 0-3 months after starting MTX administration, the median cumulative dose and improved DAS28 AUC in the good and poor response groups were 96.0 mg and 25.4 and 118.0 mg and 23.4, respectively. For 0-6 months, the median cumulative dose and improved DAS28 AUC in the good and poor response groups were 192.0 mg and 51.0 and 214.0 mg and 47.6, respectively. Statistically significant differences between the 2 groups in the 0-6-month period were observed in DAS28 AUC improvement and index R. A slight tendency for a correlation between G/G genotypes and A allele genotypes in RFC1 80 genotypes was observed, although it did not reach statistical significance.

conclusionThis study suggested that aggressive RA treatment with MTX from the early period of administration is necessary to obtain a good response after 6 months, although no SNPs predicting a better treatment response to MTX were identified.

Indexed as

DAS28Genetic polymorphismInterpatient variabilityMethotrexateRheumatoid arthritisTherapeutic response

Identifiers

PMID27274398
PMCPMC4895805
OpenAlexW2345324251

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.