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Frequency and Natural History of Inherited Bone Marrow Failure Syndromes: The Israeli Inherited Bone Marrow Failure Registry

2008· article· en· W2583625678 on OpenAlexaboutno aff
Hannah Tamary, Daniella Nishri, Joanne Yacobovich, Rama Zilber, Shraga Aviner, Polina Stepensky, Shoshana S Vilk- Ravel, Menachem Bitan, Chaim Kaplinsky, Ayelet Ben Barak, J. Kapelusnik, Ariel Koren, Carina Levin, Isaac Yaniv, Philip S. Rosenberg, Blanche P. Alter

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBone marrow failureFanconi anemiaDiamond–Blackfan anemiaPediatricsBone marrowInternal medicineAplastic anemiaCongenital NeutropeniaIncidence (geometry)SurgeryNeutropenia

Abstract

fetched live from OpenAlex

Abstract Inherited bone marrow failures syndromes (IBMFS) are rare genetic disorders usually characterized by congenital anomalies, development of bone marrow failure and a tendency to develop malignant diseases. Although single disease registries for Fanconi anemia (FA), Diamond-Blackfan Anemia (DBA), Severe Congenital Neutropenia (SCN) and Dyskeratois Congenita (DC) have been established the true incidence of many of the IBMFS is still unknown. To investigate the prevalence of each of the IBMFS and to the types and frequencies of complications we set up a retrospective national registry of these disorders in Israel. We reviewed charts of 127 patients with IBMFS diagnosed between 1964 and 2005. This represents the majority of such patients in the country. Consanguinity was recorded in 50 (40%) patients. Median time since diagnosis was 6 years (range: 1 month-39 years). Genetic analysis was available in 60 (47%) patients. The number of patients within each disease category is presented in the Table. The majority of patients who succumbed to their disease had FA. Of the 29 patients who developed malignancies (hematological and solid) the majority 23 (79%) had FA. All of the 6 patients who developed solid tumors had FA. The solid tumors were squamous cell carcinoma of head and neck, esophagus, cervix and vulva. Table: Israeli Inherited Bone Marrow Failure Cohort - Diagnosis, Complications and Survival No. of pts. FA DBA SCN CAMT DC SDS TAR NOS All Total (%) 66 (52) 18 (14) 21 (16.5) 8 (6) 6 (5) 3 (2) 3 (2) 2 (1.5) 127 (100) Per 106 people 5.3 2.6 2.1 1.1 0.86 0.43 0.29 Deceased (%) 24 (36) - 6 (29) - 2 (33) 1 (33) - - 33 (26) Molecular diagnosis (%) 34 (51) 6 (33) 7 (33) 8 (100) 4 (67) 1 (33) - - 60 (47) MDS/AML/ALL (%) 19 (29) - 4 (19) 2 (25) - - - - 25 (20) Solid tumor (%) 6 (9) - - - - - - - 6 (5) CAMT, Congenital Amegakaryocytic Thrombocytopenia; SDS-Shwachman-Diamond Syndrome; TAR, Thrombocytopenia Absent Radii; NOS-not otherwise specified. This is the largest population-based study which has examined the relative frequency of each of the IBMFS. In this cohort, FA was by far the most common form of an IBMFS (52% of pts), followed by DBA (16.5%) and SCN (14%), while CAMT, DC, SDS and TAR were far less common. These findings agree with the frequencies of FA, DBA and SCN reported by individual disease registries, and contrast with the results from the Canadian inherited marrow failure registry (Pediatr Blood Cancer47:918, 2006), where among a smaller number (39) of patients with an IBMFS the frequencies of FA, SDS, DBA and SCN were similar (12% each). One caveat is that the Israeli cohort has a large proportion of consanguineous families, which differs from most cohorts in other countries. The number of undiagnosed patients with IBMFS in our study was very small. SDS and DC are either rare in our region or under-diagnosed. The implementation of new diagnostic tests will help to resolve this issue. These data provide a rational basis for longitudinal surveillance and prevention of complications in the severe forms of IBMFS.

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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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.212
Teacher spread0.199 · 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 designObservational
Domainnot available
GenreEmpirical

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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Citations2
Published2008
Admission routes1
Has abstractyes

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