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Record W2558774850 · doi:10.3899/jrheum.161285

Willie Sutton Was Right: It’s Time to Turn to the Synovium to Drive Rheumatoid Arthritis Therapy

2016· letter· en· W2558774850 on OpenAlexvenueno aff
Eric Ruderman, Arthur M. Mandelin, Harris Perlman

Bibliographic record

VenueThe Journal of Rheumatology · 2016
Typeletter
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMedicineRheumatoid arthritisParadigm shiftMethotrexateIntensive care medicinePersonalized medicineOncologyInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

Treatments for rheumatoid arthritis (RA) have come a long way in the past 20 years. Fifteen years of widespread use of methotrexate generated a paradigm shift in the management of RA; the advent of biologic response modifiers launched the next big shift. Coupled with early, aggressive therapy, these agents have made it possible to look beyond merely controlling symptoms to a treatment landscape where remission is now a reasonable possibility for nearly 50% of our patients with early disease1. At the same time, challenges remain for appropriately using available therapies. As effective as these agents are, they do not work for all patients, and despite years of searching, we still do not have systemic biomarkers that can reliably identify those patients who will respond. Combined with the tremendous costs of these drugs, this uncertainty means that RA treatment in 2016 remains an expensive, empiric proposition. We believe that it is time for the next paradigm shift, one that does not involve new therapies, but precision, targeted application of existing and future treatments. Willie Sutton was right2. And while much work remains to be done, we believe that it will soon be time to move beyond the bloodstream and look for guidance to the most critical tissue in this disease, the synovium. One needs to look no further than the world of oncology to see the path that we must begin to take in rheumatology. In just a generation, oncologists have moved from the use of broad-based chemotherapeutic agents to personalized genetic profiling that allows them in many cases to identify the specific agent or agents most likely to effectively treat the patient’s malignancy. Cancer therapy has moved from a disease-guided approach to a pathology-guided approach, then in turn to a molecular-guided approach, in which specific molecular … Address correspondence to Dr. E.M. Ruderman, 675 North St. Clair, Suite 14-100, Chicago, Illinois 60611, USA; E-mail: e-ruderman{at}northwestern.edu

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0030.004
Scholarly communication0.0070.008
Open science0.0010.002
Research integrity0.0090.023
Insufficient payload (model declined to judge)0.0220.015

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.256
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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