Evidence map›Paper›PMID 38030397›Full record

ArticleNeurology2023

Simultaneous Comparisons of 25 Acute Migraine Medications Based on 10 Million Users' Self-Reported Records From a Smartphone Application.

Chia-Chun Chiang, Xuemin Fang, Zsolt Horvath, Francois Cadiou, Alexandre Urani, Weijie Poh, Hiroto Narimatsu, Yu Cheng, David W Dodick

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
4.9field-weighted citation impact, top 4% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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  8. Application of Artificial Intelligence in the Headache Field.Current pain and headache reports · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Chia-Chun ChiangFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0000-0001-7802-7172
Xuemin FangFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0000-0002-8540-1801
Zsolt HorvathFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0009-0009-4443-9086
Francois CadiouFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.
Alexandre UraniFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0009-0004-2519-5884
Weijie PohFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0000-0002-9700-3237
Hiroto NarimatsuFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.
Yu ChengFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0000-0003-4805-203X
David W DodickFrom the Department of Neurology (C.-C.C.), Mayo Clinic, Rochester, MN; Graduate School of Health Innovation (X.F., H.N.), Kanagawa University of Human Services, Kawasaki; IBM Client Engineering (X.F.), Banking Financial Market Unit, Chuo-Ku, Tokyo, Japan; Healint Pte. Ltd. (Z.H., F.C., A.U., W.P.), Singapore; Cancer Prevention and Cancer Control Division (H.N.), Kanagawa Cancer Center Research Institute; Department of Genetic Medicine (H.N.), Kanagawa Cancer Center, Yokohama, Japan; Department of Statistics (Y.C.), University of Pittsburgh, PA; and Department of Neurology (D.W.D.), Mayo Clinic, Scottsdale, AZ.ORCID 0000-0002-9486-6790
Kanagawa Prefectural Hospital Organization · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesMany acute treatment options exist for migraine. However, large-scale, head-to-head comparisons of treatment effectiveness from real-world patient experience reports are lacking.

methodsThis is a retrospective analysis of 10,842,795 migraine attack records extracted from an e-diary smartphone application between June 30, 2014, and July 2, 2020. We analyzed 25 acute medications among 7 classes-acetaminophen, nonsteroid anti-inflammatory drugs (NSAIDs), triptans, combination analgesics, ergots, antiemetics, and opioids. Gepants and ditan were not included in this analysis. Different doses and formulations of each medication, according to the generic names, were combined in this analysis. We used a 2-level nested logistic regression model to analyze the odds ratio (OR) of treatment effectiveness of each medication by adjusting concurrent medications and the covariance within the same user. Subgroup analyses were conducted for users in the United States, the United Kingdom, and Canada.

resultsOur final analysis included 4,777,524 medication-outcome pairs from 3,119,517 migraine attacks among 278,006 users. Triptans (mean OR 4.8), ergots (mean OR 3.02), and antiemetics (mean OR 2.67) were the top 3 classes of medications with the highest effectiveness, followed by opioids (mean OR 2.49), NSAIDs (other than ibuprofen, mean OR 1.94), combination analgesics (acetaminophen/acetylsalicylic acid/caffeine) (OR 1.69, 95% CI 1.67-1.71), others (OR 1.49, 95% CI 1.47-1.50), and acetaminophen (OR 0.83, 95% CI 0.83-0.84), using ibuprofen as the reference. Individual medications with the highest ORs were eletriptan (OR 6.1, 95% CI 6.0-6.3), zolmitriptan (OR 5.7, 95% CI 5.6-5.8), and sumatriptan (OR 5.2, 95% CI 5.2-5.3). The ORs of acetaminophen, NSAIDS, combination analgesics, and opioids were mostly around or less than 1, suggesting similar or lower reported effectiveness compared with ibuprofen. The ORs for 24 medications, except that of acetylsalicylic acid, achieved statistical significance with DISCUSSION: Using a big data approach, we analyzed patient-generated real-time records of 10 million migraine attacks and conducted simultaneous head-to-head comparisons of 25 acute migraine medications. Our findings that triptans, ergots, and antiemetics are the most effective classes of medications align with the guideline recommendations and offer generalizable insights to complement clinical practice. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that for patients with migraine, selected acute medications (e.g., triptans, ergots, antiemetics) are associated with higher odds of user-rated positive response than ibuprofen.

Indexed as

AntiemeticsMigraine DisordersAcetaminophenAnalgesics, OpioidAnti-Inflammatory Agents, Non-SteroidalAspirinHumansIbuprofenRetrospective StudiesSelf ReportSmartphoneTryptaminesAcetaminophenAnalgesics, OpioidAntiemeticsAnti-Inflammatory Agents, Non-SteroidalAspirinIbuprofenTryptamines

Identifiers

PMID38030397
PMCPMC10791049
OpenAlexW4389120464

What OpenQuestion holds

Textmetadata
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.