Understanding Neutropenia: The 20 Year Experience of the Severe Chronic Neutropenia International Registry (SCNIR)
Bibliographic record
Abstract
Abstract Background: In 1994 Severe Chronic Neutropenia International Registry (SCNIR) opened for enrollment of patients with at least 3 absolute neutrophil counts (ANC) less than 0.5 x 109/L during a three month period. At that time severe chronic neutropenia (SCN) was categorized as cyclic, congenital, autoimmune or idiopathic based largely on clinical criteria. A randomized trial had established effectiveness of treatment with granulocyte colony-stimulating factor (G-CSF), but long-term consequences of such treatment were unknown. Hypothesis: We began the SCNIR based on the hypothesis that underlying pathophysiology, natural history of patients with chronic neutropenia and benefits and risk of G-CSF therapy could only be accurately established through an international registry with long term follow-up of patients with these rare hematological disorders. Methods: SCNIR enrollment requires informed consent, ANC<0.5 x 109/L at least 3 times over a 3 month period, neutropenia not due to known systemic autoimmune disease (e.g., lupus, rheumatoid arthritis), cancer or cancer chemotherapy. There is a centralized enrollment process directed through offices in the US (Seattle) and Germany (Hannover). Continued enrollment requires annual follow-up information, i.e., clinical status, treatments and blood counts, and bone marrow reports for some categories of patients. Data on pregnancies, stem cell transplantation (SCT), non-hematological features and complications are also collected on standardized forms for subsets of patients. Comprehensive immunological assessments and genetic testing are encouraged but not required for enrollment. For some patient groups, e.g., Shwachman-Diamond syndrome (SDS) and Barth syndrome, the SCNIR now enrolls patients without severe neutropenia to gain perspectives on long-term outcomes for these disorders. Since 1994 the SCNIR has enrolled more than 2000 patients; 174 died, 193 resolved neutropenia, 543 withdrew or were lost to follow-up and almost all others continue in this long term observation study. The median follow-up for enrolled patients is now almost 10 years. The most common patient categories are idiopathic, cyclic (CyN) and congenital neutropenia (CN); 68% of CyN and 65% of CN patients having sequencing studies have mutations in ELANE. Some specific mutations are associated with high frequency (>90%) of severe outcomes (e.g. MDS/AML, failure to respond to G-CSF, death from infections, need for stem cell transplant) often many years after SCNIR enrollment and beginning G-CSF therapy. GSD1 patients improve with G-CSF treatment, but experience splenomegaly and continued problems with infections or complications. The SCNIR through a SDS sub-registry is redefining Shwachman-Diamond syndrome; only about one-half of enrollees have “classic” presentation and a substantial number with “classic presentation” lack mutations in SBDS. The SCNIR is participating in an NIH trial of a CXCR4 antagonist for treatment of WHIM syndrome, as an example of molecularly targeted treatment for this rare disease. The SCNIR is also the key resource for discovery of genetic causes for congenital neutropenia, e.g., G6PC3, HAX1, and TCIRG1 and others, recognition of differences in frequency of autosomal dominant and recessive SCN in populations of Europe and North America and identifying congenital neutropenia cases of unknown cause. Genetic testing has also broadened the clinical spectrum of these disorders. Conclusions: Through the efforts of patients, families, physicians, nurses and investigators, and with support from the NIH, industry, and private philanthropy, chronic neutropenia is now far better understood at the genetic, molecular and cellular level than 20 years ago. Treatment responses to G-CSF are well characterized; novel therapies are emerging; and the prognosis for patients with SCN appears to be improving. The knowledge gained through the SCNIR and availability of G-CSF has redefined clinicians’ approach to chronic neutropenia. The SCNIR is a model of international research collaboration to understand rare diseases in hematology and other areas of medicine. Broad enrollment criteria, physician, patient and family participation, a dedicated staff, and continuing cooperation underlie success of the SCNIR and this model to understanding rare diseases. Disclosures Dale: Amgen: Consultancy, Honoraria, Research Funding. Boxer:Amgen: Equity Ownership. Morrow:Amgen: Employment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".