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Record W2157580101 · doi:10.1002/ajh.23287

Immune thrombocytopenia: Getting back to basics

2012· letter· en· W2157580101 on OpenAlexafffund
Donald M. Arnold

Bibliographic record

VenueAmerican Journal of Hematology · 2012
Typeletter
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversityCanadian Blood Services
FundersCanadian Institutes of Health Research
KeywordsMedicineSplenectomyRituximabThrombocytopenic purpuraImmune systemImmune thrombocytopeniaImmunologyPediatricsPlateletAntibodySpleen

Abstract

fetched live from OpenAlex

Immune thrombocytopenia (ITP) is an autoimmune disorder characterized by a low platelet count and an increased risk of bleeding. The first report of what was possibly ITP dates back to 1557 in a description of a boy "with dark macules, resembling flea bites, had no fever and for several days had bloody discharges, eventually recovering" [1]. Two centuries later, Paul Werlhof described the disorder under the name of Morbus Maculosus Hemorrhagicus, which later became known as M. Maculosus Werlhofii after the physician who first classified it. It wasn't until the ability to readily count platelets and the first successful splenectomy in 1916 that the modern day version of idiopathic thrombocytopenic purpura—recently renamed immune thrombocytopenia—became known. Treatment options for ITP remained fairly limited for the next few decades, consisting mainly of corticosteroids [2], splenectomy, and later intravenous immune globulin [3]; a far cry from the first prescription of "moderate exercise in the open air, a generous diet, and the free use of wine" (Robert Willan, 1808). However, in the last decade, interest in ITP has been renewed mainly because of the introduction of novel treatments including rituximab [4] and the thrombopoietin receptor agonists [5, 6]. This led to increased awareness, clinical trials, and a re-examination of pathophysiology [7]. The result has been a fresh new look at an old disease. And as we begin to peel away the surface of ITP once again, it is becoming more and more evident how little we still know about it—starting with: how common is the problem? To answer this fundamental question, one needs to start with a definition. However, even that is no easy task when it comes to ITP. Perhaps a testament to how far we are from a precise definition is that there still is no diagnostic test, and investigations of patients suspected of having ITP are used to rule out other disorders, rather than to rule in ITP [8]. The lack of disease-defining features is evident; besides thrombocytopenia and the bleeding manifestations that may ensue, there are generally no physical findings, no other blood count derangements, and (under properly controlled conditions) no specific abnormalities on routine bone marrow examinations. On the other hand, some patients can be distinguished by mild splenomegaly, antiplatelet antibodies and increased bone marrow megakaryocytes. Furthermore, serological and molecular studies have demonstrated that some patients have unique cytokine profiles or abnormal regulatory T-cells [9]. These clinical and basic studies suggest that ITP is a heterogeneous disorder with distinct subsets of patients. In this context, the "ITP syndrome" [10] may be the final common pathway for a variety of underlying pathologies characterized by low platelet counts. The nature of the ITP illness poses additional barriers to its proper classification. First, it is relatively uncommon; second, patients are generally not organized into specialized referral clinics rendering enrolment in clinical trials challenging [11]; and third, the disease occurs on a wide spectrum ranging from asymptomatic thrombocytopenia to life-threatening bleeding. Rigorous methods are needed to classify, enumerate, and describe ITP, which invariably will include handling large patient databases. Recent initiatives have provided a framework for the diagnosis and management of patients. Recommendations from the International Working Group on the standardization of terminology provided a new platelet count threshold (below 100 × 109/L platelets) and new definitions of disease stage, severity, and treatment response [12]; and the American Society of Hematology-endorsed evidence-based practice guidelines helped to position new therapies in the context of conventional ones, including splenectomy [8]. In two papers appearing in this issue of the "American Journal of Hematology," Dr. Terrell et al. have gone even further back to basics by devising a strategy to accurately identify patients with ITP from medical records [13], and then applying that strategy to estimate disease frequency in the state of Oklahoma [14]. The authors established levels of evidence for a diagnosis of ITP (definite, probable, or unlikely), reminiscent of clinical grading systems that have been used in other areas of hematology including drug-induced immune thrombocytopenia [15], heparin-induced thrombocytopenia [16], and deep vein thrombosis [17]. They found that limiting the source of data to hematologists' practices and to outpatient visits captured most patients with ITP. Their methods demonstrate rigor in the identification of patients, and highlight the inherent challenges of applying such a strategy to a disease that lacks defining features. For example, by their criteria, the diagnosis of ITP was considered unlikely if a hematologist described "thrombocytopenia" in an adult without specifically stating the diagnosis. Many hematologists might accurately use such a description for patients with mild or moderate ITP. Armed with their validated definition, the authors then set out to determine the frequency of ITP without restrictions, something that had previously only been done using databases of managed health care plans, limited to age groups or by point-prevalence questionnaires [18-21]. The authors found that the average annual prevalence of ITP was 8.1 per 100,000 children and 12.1 per 100,000 adults. The prevalence of ITP increased in older adults and was more common in females, except in the cohort aged 70 years or older, which showed a male predominance. While these numbers apply to the state of Oklahoma, they likely represent an accurate estimate of the burden of ITP in North America, if not most of the developed world. Prevalence and incidence data and the methods used to derive them will now need to be adjusted to disease severity so that the impact of severe ITP can be isolated from patients who may never require treatment. The series of papers by Terrell et al. is a rigorous, back-to-basics approach to an age old disease that is only now being redefined. The landscape of ITP is shifting and refined epidemiological studies such as these are needed to improve classification systems and further our understanding of pathophysiology. Ultimately, such research will help identify those patients who stand to benefit most from treatment.

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)0.004
metaresearch head score (Gemma)0.013
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.001
Science and technology studies0.0010.006
Scholarly communication0.0050.009
Open science0.0020.002
Research integrity0.0060.017
Insufficient payload (model declined to judge)0.0110.006

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 head0.016
GPT teacher head0.285
Teacher spread0.268 · 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".

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Citations9
Published2012
Admission routes2
Has abstractyes

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