Evidence map›Paper›PMID 42598053›Full record

ArticleFrontiers in medicine2026

The road from standardized to personalized medicine: the difficult-to-treat framework as a critical waystation.

Lilla Gunkl-Tóth, Csaba Fűr-Kovács, György Nagy

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Lilla Gunkl-TóthDepartment of Rheumatology and Immunology, Semmelweis University, Budapest, Hungary.
Csaba Fűr-KovácsAcademyEX Education Limited Partnership, Auckland, New Zealand.
György NagyDepartment of Rheumatology and Immunology, Semmelweis University, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Standardized care has become the cornerstone of modern medicine. However, many patients remain symptomatic despite following the appropriate guidelines and the application of treatment escalation, and become difficult-to-treat (D2T). The D2T concept can also provide a framework for identifying when standard care is no longer sufficient and when individualized management becomes clinically justified. Rather than reflecting therapeutic failure alone, the D2T state can be a consequence of various reasons, including underlying biological, clinical, psychosocial, or contextual complexity, which draws attention to the importance of multidomain reassessment in these conditions. Combined with emerging artificial intelligence-based trajectory recognition, the D2T framework may support earlier identification of complex patients and more selective implementation of precision strategies. In this way, the D2T concept can be understood as a practical bridge between standardized medicine and individualized care, with a potential relevance as a cross-disciplinary framework.

Indexed as

artificial intelligencedifficult-to-treat areamedicinepersonalized medicineprecision medicine

Identifiers

PMID42598053
PMCPMC13470244

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.