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1314 Recursive Partitioning As a Tool for Differential Diagnosis between Acquired and Inherited Bone Marrow Failure Syndromes (BMF)

Program: Oral and Poster Abstracts
Session: 508. Bone Marrow Failure: Acquired: Poster I
Hematology Disease Topics & Pathways:
Acquired Marrow Failure Syndromes, Bone Marrow Failure Syndromes, Inherited Marrow Failure Syndromes, Aplastic Anemia, Diseases
Saturday, December 7, 2024, 5:30 PM-7:30 PM

Eléonore Kaphan, MD1*, Anouk Walter Petrich, MD2*, Lise Larcher3*, Thierry Leblanc4*, Mony Fahd, MD MSc5,6*, Benedicte Bruno7*, Edouard Forcade, MD, PhD8*, Cecile Renard, MD9*, Arthur Sterin10*, Michael Loschi, MD, PhD11*, Elodie Lainey, PhD, PharmD12*, Jean Soulier, MD13,14*, Caroline Kannengiesser15*, Gerard Socie, MD, PhD16,17,18, Regis Peffault De Latour1,19,20,21,22*, Jerome Lambert, MD, PhD23* and Flore Sicre de Fontbrune, MD24*

1Hematology / Transplantation, Hospital St Louis, Paris, France
2Biostatistics and Medical Information Department, Saint Louis University Hospital, AP-HP, Université Paris Cité, Paris, France
3Hopital Saint-Louis and University De Paris, Paris, FRA
4Service d’Hematologie et d’Immunologie Pédiatrique, Centre de Reference Aplasies Medullaires Acquises et Constitutionnelles, Hôpital Robert-Debré, Assistance Publique Hôpitaux de Paris and Université Paris Cité, Paris, France
5Saint-Louis Academic Hospital, GHU Ap-HP Nord Université Paris Cité, French National Reference Center for Severe Aplastic Anemia, Paris, France
6Pediatric hematology and immunology department, Robert-Debré Hospital, GHU APHP Nord Université Paris-Cité, Paris, France
7Chru Lille, Jeanne De Flandre Hématologie Pédiatrique, Lille, FRA
8Service d'Hématologie Clinique et Thérapie Cellulaire, CHU Bordeaux, Hopital Haut-Leveque, Pessac, France
9Institute of Hematology and Pediatric Oncology, Lyon, France
10Department of Pediatric Hematology, Immunology and Oncology, APHM, La Timone Children Hospital, Department of Pediatric Hematology, Immunolog, Marseille, France
11Hematology Department, Nice University Hospital, Nice, France
12Robert Debre Hospital, Paris, FRA
13Hopital Saint-Louis Centre Hayem 2ETG, Paris, France
14INSERM U944/CNRS UMR7212, Institut de Recherche Saint-Louis, Paris, France
15Assistance Publique-hôPitaux De Paris, Bichat, Paris, FRA
16INSERM UMR 976, Université Paris Cité, Institut de Recherche Saint-Louis (IRSL), Paris, France
17Hematology / Transplantation, Hematology Transplantation, Paris, France
18French Reference Center for Aplastic Anemia and Paroxysmal Nocturnal Hemoglobinuria, Saint Louis Hospital and University Paris Diderot, Paris, France
19French Reference Center for Aplastic Anemia and Paroxysmal Nocturnal Hemoglobinuria, Paris, France
20Hematology Branch, NHLBI, NIH, Bethesda, MD
21Severe Aplastic Anemia Working Party, European Group for Blood and Marrow Transplantation (EBMT), Leiden, Netherlands
22Société Française de Greffe de Moelle et de Thérapie Cellulaire (SFGM-TC), Hôpital Henri Herriot, CHU, Lyon, France
23Hôpital Saint Louis, Biostatistics and Medical Information Department, Saint Louis University Hospital, AP-HP, Université Paris Cité, Paris, FRA
24Centre de Référence Aplasie Médullaire, Service d’Hématologie Greffe, Assistance Publique des Hôpitaux de Paris, Hôpital Saint-Louis, Paris, France

Background

Distinguishing inherited BMF (IBMF) and acquired aplastic anemia (aAA) at diagnosis is a major clinical challenge and essential for determining appropriate initial treatment. However, no specific test can unequivocally affirm aAA, and the diagnosis of IBMF requires time consuming genetic analyses, may have limited availability, and thus can lead to detrimental delay of treatment initiation by immunosuppressive treatment (IST) or transplantation. The objective of our study was to develop a practical scoring system to identify patients who are unlikely to have IBMF and therefore may not systematically require genetic analysis before starting treatment.

Methods

The model was trained on a cohort from Robert-Debré and St-Louis Hospital and was validated on a large independent cohort (all these informations are gathered in a nationwide data base; RIME, after informed consent). Patients were classified as having either aAA or IBMF based on genetic results (chromosome breakage, pathogenic inherited variants by Next Generation Sequencing (dedicated IBMF NGS panel), Pr Soulier, St-Louis Hospital) and/or their response to IST. We retrospectively recorded 33 clinical and laboratory characteristics at the time of diagnosis and 15 were considered as candidate for a diagnostic algorithm. The diagnostic algorithm was then constructed using recursive partitioning (classification and regression tree). Model sensitivity represents the ability to correctly identify aAA among true aAA, whereas specificity represents the ability to correctly diagnostic IBMF among true IBMF. The positive predictive value was the probability of true aAA among those with a positive result for aAA according to the diagnostic algorithm.

We decided to integrate in the model mean age, previous history of inflammatory or auto-immune disease, post-hepatitis BMF, BMF during pregnancy, familial history of cytopenia, cytogenetics abnormality, cytogenetics failure, mean corpuscular volume, mean serum alpha-fetoprotein level and variables which differ in univariate analysis. Acute onset of BMF was defined as history or worsening of cytopenia within 1 year.

Results

The training set included 150 patients. Median age was 35 years (range 2.2-91), and 61.3% were male: 133 with aAA and 17 with IBMF. Three of the 15 variables of interest were selected by the model in the final algorithm: clinical morphological abnormalities, PNH clone, and acute onset of BMF. This algorithm achieved in the training cohort a sensitivity of 96.2% (IC95%: 91.4-98.8%) and a specificity of 82.4% (IC95%: 56.6-96.2) in the ability to correctly differentiate aAA from IBMF. We then applied the algorithm to the validation cohort of 489 patients with at least 2 non-missing data among the 3 variables of interest (aAA n=383 (78.3%); IBMF n= 106 (21.7%)) and obtained similar sensitivity of 94.3% (IC95: 91.4-96.4) and specificity of 85.8% (IC95: 77.7-91.9) with a positive predictive value of 96.0% (IC95: 93.5-97.8). A sensitivity analysis on the subgroup of 129 patients of the validation cohort who underwent genetic testing at initial diagnosis (NGS IBMF and/or Fanconi chromosomal breakage analysis) led to similar results.

Conclusions

We developed an efficient and practical scoring system that incorporates 3 routine clinical and laboratory parameters (clinical morphological abnormalities, acute onset of cytopenia and the presence of a PNH clone) to identify patients who might not require genetical analysis before starting treatment at sensitivity level of 94.3%, and positive predictive value of 96.0%.

Disclosures: Kaphan: Alexion: Honoraria. Forcade: Novartis: Consultancy; Alexion: Other: Travel support, Speakers Bureau; Maat Pharma: Consultancy; Astellas: Research Funding; Gilead: Other: Travel support, Speakers Bureau; GSK: Speakers Bureau; Jazz: Speakers Bureau; Novartis: Other: Travel support, Speakers Bureau; Sanofi: Other: Travel support, Speakers Bureau; Sobi: Speakers Bureau. Renard: Pierre Fabre: Honoraria, Other: travels; Medac: Consultancy, Honoraria; Jazz pharmaceuticals: Consultancy, Honoraria. Peffault De Latour: Apellis Pharmaceuticals: Consultancy, Honoraria; Amgen: Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Alexion: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Swedish Orphan Biovitrum AB: Consultancy, Honoraria. Sicre de Fontbrune: Sobi: Honoraria, Research Funding; Alexion, AstraZeneca Rare Disease: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Samsung: Honoraria, Research Funding.

*signifies non-member of ASH