Development and Validation of the PASS Score: A Simplified Tool to Diagnose Acquired Aplastic Anemia in Adults

Development and Validation of the PASS Score: A Simplified Tool to Diagnose Acquired Aplastic Anemia in Adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Development and Validation of the PASS Score: A Simplified Tool to Diagnose Acquired Aplastic Anemia in Adults Gabriel Aleixo, HeeJin Cheon, Jiayin Zheng, Stephanie Soewito, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7725283/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Apr, 2026 Read the published version in Leukemia → Version 1 posted 6 You are reading this latest preprint version Abstract Acquired aplastic anemia (AA) can present similarly to inherited bone marrow failure syndromes (IBMFS) but treatment differs. AA diagnosis relies on excluding IBMFS; however, genetic testing is not always available, may delay care or be inconclusive. We developed the Predictive Aplastic Score System (PASS), a clinical tool using readily available data to distinguish AA from IBMFS in adults. The training cohort included 212 adults (162 AA, 50 IBMFS). Compared to IBMFS, AA patients were older and more likely to have acute-onset, severe cytopenias. Using logistic regression with LASSO, we selected seven clinical variables for model inclusion: severity, acuity, age, IBMFS red flags, AA-associated conditions, AA-associated somatic changes, and telomere lengths. The model achieved AUC of 0.990 (95% CI: 0.982–0.999), with 100% positive predictive value (PPV) for AA for scores ≥ 30. 86.8% of patients with scores < 0 had IBMFS. We validated PASS in 716 patients from four external cohorts with AUC of 0.977 (95% CI: 0.968–0.987). Threshold analysis confirmed 100% PPV for scores ≥ 30, rapidly diagnosing 80% of AA cases. PASS is a practical and accurate clinical tool that can rapidly distinguish AA from IBMFS for most adult patients. To promote clinical adoption, we developed open-access web calculator ( https://pennmedicine.shinyapps.io/passcalc/ ). Health sciences/Diseases/Haematological diseases/Anaemia Health sciences/Medical research/Translational research Health sciences/Health care/Diagnosis/Genetic testing Health sciences/Pathogenesis/Immunopathogenesis Health sciences/Signs and symptoms aplastic anemia inherited bone marrow failure telomere PNH IBMFS 6pLOH 6p CN-LOH BCOR Del13q diagnostic score diagnosis diagnostic tool PASS PASS score Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Full Text Additional Declarations There is NO conflict of interest to disclose. Supplementary Files 456891supp886973t80psxconvrtFinalSupplement.pdf FINALRevisedAppendixCLEANwithdatasetsforsubmission.pdf Supplemental Appendix Cite Share Download PDF Status: Published Journal Publication published 26 Apr, 2026 Read the published version in Leukemia → Version 1 posted Editorial decision: revise 28 Jan, 2026 Reviewers invited by journal 16 Jan, 2026 Submission checks completed at journal 14 Jan, 2026 First submitted to journal 08 Jan, 2026 Unknown event 08 Jan, 2026 Editor assigned by journal 29 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7725283","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":575865544,"identity":"b7293e8c-bae5-4115-ad28-5d0d3163c08e","order_by":0,"name":"Gabriel Aleixo","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"","lastName":"Aleixo","suffix":""},{"id":575865545,"identity":"2a859da3-04cd-434b-817e-7a080a932ea1","order_by":1,"name":"HeeJin Cheon","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"HeeJin","middleName":"","lastName":"Cheon","suffix":""},{"id":575865546,"identity":"2946077c-d1dc-4871-8f89-929dd01b88ac","order_by":2,"name":"Jiayin Zheng","email":"","orcid":"https://orcid.org/0000-0002-5559-6847","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Jiayin","middleName":"","lastName":"Zheng","suffix":""},{"id":575865547,"identity":"99967302-3f66-418f-96a8-0106822afc1b","order_by":3,"name":"Stephanie Soewito","email":"","orcid":"","institution":"The University of Texas MD Anderson Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Stephanie","middleName":"","lastName":"Soewito","suffix":""},{"id":575865548,"identity":"f4d7098b-b54c-4244-b423-7b98ed8025d1","order_by":4,"name":"Jimmy Lee","email":"","orcid":"https://orcid.org/0009-0003-0789-8941","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jimmy","middleName":"","lastName":"Lee","suffix":""},{"id":575865562,"identity":"ee6485fa-5059-4a0f-95f5-20f6c7fa231a","order_by":5,"name":"Eléonore Kaphan","email":"","orcid":"","institution":"Hôpital Saint‐Louis","correspondingAuthor":false,"prefix":"","firstName":"Eléonore","middleName":"","lastName":"Kaphan","suffix":""},{"id":575865549,"identity":"9e212196-502e-43b9-8fbc-bcc86774cbcf","order_by":6,"name":"Neha Kalakuntla","email":"","orcid":"https://orcid.org/0000-0001-7999-3081","institution":"UT Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Neha","middleName":"","lastName":"Kalakuntla","suffix":""},{"id":575865550,"identity":"5b4437a5-551c-454f-9907-502e6f96cbbe","order_by":7,"name":"Wei-Ying Jen","email":"","orcid":"https://orcid.org/0000-0002-9339-3362","institution":"The University of Texas MD Anderson Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Wei-Ying","middleName":"","lastName":"Jen","suffix":""},{"id":575865551,"identity":"e7c36a49-2f01-4579-afd1-c191de156667","order_by":8,"name":"Sumasri Kotha","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Sumasri","middleName":"","lastName":"Kotha","suffix":""},{"id":575865552,"identity":"225b5704-eb5f-4a00-bb55-1e7c0a9608ee","order_by":9,"name":"Alex Rupsee","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Alex","middleName":"","lastName":"Rupsee","suffix":""},{"id":575865554,"identity":"636f7f69-1ed4-4641-bb9d-367ffb7f2610","order_by":10,"name":"Mia Djulbegovic","email":"","orcid":"","institution":"University of Pennsylvania","correspondingAuthor":false,"prefix":"","firstName":"Mia","middleName":"","lastName":"Djulbegovic","suffix":""},{"id":575865555,"identity":"2828ade4-ace5-4f85-a1ef-659997414281","order_by":11,"name":"Jairo A. 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Bar plot showing numbers of patients with severe or very severe aplastic anemia (SAA/VSAA, teal) and non-severe aplastic anemia (NSAA, orange) among those with AA and IBMFS. B) Shown is the distribution of ages (in years) at the time of bone marrow failure diagnosis, with orange dots showing patients presenting with NSAA and teal for those presenting with SAA/VSAA. The dashed line marks the 60-year age, which was used for subsequent regression analyses. C) Acuity of presentation, defined by the duration of cytopenias from the first abnormal CBC to diagnosis. Patients with AA typically presented acutely, defined as within 1 year of cytopenia onset, whereas those with IBMFS more often had a chronic course extending beyond 1 year. Disease severity is also indicated by orange (NSAA) and teal (SAA/VSAA) dots. \u0026nbsp;The dashed line marks the 1-year threshold used to define acute versus chronic presentation\u003cstrong\u003e. \u003c/strong\u003eD-E) Median telomere lengths in lymphocytes (D) and granulocytes (E) measured by flow-FISH analysis for 77 AA (blue dots) and 39 IMBFS patients (red dots) with available raw telomere lengths data. Telomere length distributions from healthy controls are shown for reference (gray dots), based on published data from Johns Hopkins (n = 192) and Vancouver (n = 444), with percentile curves in orange (1st, 10th, 50th, 90th, and 99th percentiles, from bottom to top). To the right of each telomere length scatter plot are the corresponding summary analysis depicted in stacked bar plots showing the number of AA and IBMFS patients with telomeres \u0026lt;1\u003csup\u003est\u003c/sup\u003e percentile in lymphocytes (in D), and granulocytes (in E).\u0026nbsp; Statistical significance was determined using Fisher’s exact test for categorical variables (panels A, D, and E) and two-sided Student’s t tests for continuous variables (panels B and C). p values are indicated as follows: **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001; **** p \u0026lt; 0.0001 (****). F) Schematic demonstrating the PASS score calculation. The PASS score is calculated by adding individual criteria contributions from seven clinical factors:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(1)\u003c/strong\u003e Cytopenia severity, with \u003cstrong\u003e+20 points\u003c/strong\u003e assigned for SAA/VSAA (defined as two or more of the following: absolute neutrophil count (ANC) \u0026lt; 0.5·103 cells/μL, anemia with an absolute reticulocyte count \u0026lt;60·103 cells/μL, platelets \u0026lt; 20·103 cells/μL), and \u003cstrong\u003e0 points\u003c/strong\u003e assigned for NSAA (defined as having one or fewer severe cytopenias defined above).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e(2) \u003c/strong\u003eAcute presentation, defined as cytopenias of 1 year or less in duration are assigned \u003cstrong\u003e+10 points\u003c/strong\u003e. Chronic presentation, defined as cytopenias \u0026gt;1 year duration, are assigned either\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; -10 points\u003c/strong\u003e in patients with SAA/VSAA cytopenias, or \u003cstrong\u003e-20 points\u003c/strong\u003e in patients with NSAA cytopenias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(3) \u003c/strong\u003ePatients being evaluated at 60 years and older are given\u003cstrong\u003e +10 points\u003c/strong\u003e, while those under 60 years at the time of evaluation are assigned \u003cstrong\u003e0 points\u003c/strong\u003e in patients with SAA/VSAA cytopenias or \u003cstrong\u003e-10 points\u003c/strong\u003e in patients with NSAA cytopenias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(4) \u003c/strong\u003eIBMFS red flag is assigned \u003cstrong\u003e-20 points\u003c/strong\u003e if any of the red flag conditions are present; patients are assigned \u003cstrong\u003e+10 points \u003c/strong\u003eif there are no red flags. IBMFS red flag is defined as having any of the following i) congenital abnormality, including abnormal thumb, or dysmorphic features, ii) Interstitial lung disease, avascular necrosis, or unexplained liver cirrhosis, iii) Mucocutaneous triad of nail dystrophy, skin hyperpigmentation, oral leukoplakia, iv) Unexpected hematologic toxicity with failure to recover blood counts after chemotherapy or radiation, v) Refractory warts or a history of non-TB mycobacterial infection, vi) Squamous cell cancer of the head and neck or anogenital region, vii) First-degree relative with a diagnosis of bone marrow failure or thrombocytopenia, MDS, AML, or one of the red flag conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(5) \u003c/strong\u003ePresence of rare conditions etiologically related to AA or incompatible with IBMFS (“AA-associated conditions”) is assigned \u003cstrong\u003e+10 points\u003c/strong\u003e. Absence of these conditions is given \u003cstrong\u003e0 points\u003c/strong\u003e. AA-associated conditions are defined as: i) Seronegative autoimmune hepatitis, ii) Treatment with immune checkpoint inhibitors, iii) Known diagnosis of immune dysregulation syndrome (e.g., CTLA4 haploinsufficiency), iv) History of eosinophilic fasciitis, v) History of thymoma, vi) History of Hodgkin’s lymphoma, vii) Patient previously tolerated cytotoxic chemotherapy without unexpected hematologic toxicity (e.g., historical treatment for breast cancer or lymphoma) non-contiguous to current episode of BMF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(6) \u003c/strong\u003ePresence of clonal hematopoiesis of AA-associated acquired somatic changes is assigned \u003cstrong\u003e+20 points\u003c/strong\u003e: PNH granulocyte clone ≥0.5% acquired 6p loss of heterozygosity (6pLOH), del(13)(q) as an isolated abnormality, and somatic mutation in \u003cem\u003eBCOR\u003c/em\u003e or \u003cem\u003eBCORL1\u003c/em\u003e genes.\u0026nbsp; Absence of these is given \u003cstrong\u003e0 points\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(7) \u003c/strong\u003eMedian lymphocyte telomere lengths \u0026lt;1\u003csup\u003est\u003c/sup\u003e percentile are given \u003cstrong\u003e-20 points\u003c/strong\u003e, while longer telomere lengths of 1\u003csup\u003est\u003c/sup\u003e percentile and higher are given\u003cstrong\u003e 0 points\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eNote: Of the 7 individual score criteria, factors 1-5 are required. Factors 6 and 7 are optional and can be added for greater diagnosis accuracy as they become available. Missing values are assigned 0.\u003c/p\u003e","description":"","filename":"RevisedFig1trainingplusscorematrixsmaller.png","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/aed4164f15edc31b07fc3879.png"},{"id":100854344,"identity":"590b951f-6682-489e-890f-117b44553787","added_by":"auto","created_at":"2026-01-22 06:52:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1646403,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe PASS model performance in the training cohort. A)\u003c/strong\u003e The ROC curve, showing the sensitivity (true positive rate) on the Y-axis against the false positive rate (1 − specificity) on the X-axis for scores generated with the PASS model in the training cohort. The red dots correspond to labeled scores in the training cohort. Ideal discrimination allows perfect sensitivity without false positives (upper left quadrant). The dashed diagonal line indicates no discrimination between true and false positives (random). The PASS score shows an excellent area under the curve (AUC), indicating near-perfect diagnostic performance.\u003cstrong\u003e \u003c/strong\u003eBlue arrow points to the score of 30, and red arrow to the score of 0, which were chosen as score thresholds for PASS. \u003cstrong\u003eB)\u003c/strong\u003e A plot demonstrating the PASS score performance characteristics (plotted on the Y-axis) across a range of score thresholds (on the X-axis). Plotted are the PPV (light blue), specificity (dark blue), NPV (light green), and sensitivity (dark green). The dashed vertical lines are shown at a score of 30 (demarcating scores with 100% PPV and specificity for AA), and at a score of 0 (demarcating a threshold below which the probability of an AA diagnosis starts to sharply fall and IBMFS diagnosis is more likely). \u003cstrong\u003eC)\u003c/strong\u003e This panel shows a calibration plot comparing predicted probability of AA derived from a logistic regression model (PASS score as predictor) on x-axis with observed frequency of AA on the y-axis. Each point represents a bin of rounded predicted probabilities, annotated with average PASS score and sample size. The dashed diagonal line indicates perfect calibration. The shaded blue region reflects a LOESS-smoothed fit with 95% confidence interval. Green and red annotations highlight regions of systematic underestimation and overestimation, respectively. The model performs well at the extremes, where very low and very high predicted probabilities align with observed outcomes. Arrow points to the region of the plot corresponding to the threshold of 30. \u003cstrong\u003eD) \u003c/strong\u003eDistribution of AA and IBMFS diagnoses across the range of PASS scores (on X-axis), demonstrating excellent separation between the two diagnostic categories, with high specificity for AA for positive PASS scores of 30 and higher. \u003cstrong\u003eE) \u003c/strong\u003eProportion of AA and IBMFS diagnoses across the range of PASS scores, showing that lower scores are strongly enriched for IBMFS while higher scores are enriched for AA, with near-complete separation at thresholds above 20.\u003c/p\u003e","description":"","filename":"RevisedFINALFig2smaller.png","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/b81462ad4dc357074845fd51.png"},{"id":100859351,"identity":"b3f79e1d-22d7-4b20-a5a8-36068d2df384","added_by":"auto","created_at":"2026-01-22 07:27:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4441355,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe PASS model performance in four external validation cohorts. \u003c/strong\u003ePanels are grouped by cohort: \u003cstrong\u003eA–C:\u003c/strong\u003e RIME, \u003cstrong\u003eD–F:\u003c/strong\u003e NIH/USP\u003cstrong\u003e, G–I:\u003c/strong\u003e MDA, \u003cstrong\u003eJ–L:\u003c/strong\u003e UTSW, and \u003cstrong\u003eK-O:\u003c/strong\u003e combined cohort. \u003cstrong\u003eA, D, G, J, K)\u003c/strong\u003eROC curves showing sensitivity (Y-axis) versus false positive rate (X-axis) for PASS scores in each validation cohort. Red dots indicate labeled scores from the training cohort. The dashed diagonal line represents random classification; ideal discrimination lies in the upper left quadrant. Across all cohorts, the PASS model demonstrates excellent diagnostic performance, with high area under the curve (AUC), reflecting strong separation between AA and IBMFS\u003cstrong\u003e. B, E, H, K)\u003c/strong\u003e Distribution of AA and IBMFS diagnoses across PASS scores. AA diagnoses cluster at higher scores, with only AA diagnoses scoring at 30 and higher, and IBMFS clustering at lower scores. \u003cstrong\u003eC, F, I, L)\u003c/strong\u003e Diagnostic performance metrics across score thresholds, including PPV (light blue), specificity (dark blue), NPV (light green), and sensitivity (dark green). Vertical dashed lines mark thresholds of 0 and 30, which delineate low and high likelihood of AA, respectively. Scores ≥30 yield 100% PPV and specificity for AA, while scores \u0026lt;0 are associated with a sharp decline in AA probability and increased likelihood of IBMFS. These patterns were consistent across all three validation cohorts.\u003cstrong\u003eN)\u003c/strong\u003e Proportion of AA and IBMFS diagnoses across the range of PASS in the combined validation cohort. Lower PASS scores were predominantly associated with IBMFS, while higher scores were enriched for AA, with near-complete separation achieved at thresholds above 20. \u003cstrong\u003eO) \u003c/strong\u003eCalibration plot for the combined validation cohorts, comparing predicted probability of AA (X-axis) with observed frequency (Y-axis). The dashed diagonal line indicates perfect calibration. A LOESS-smoothed fit with 95% confidence interval is shown within the blue shaded region.\u003cstrong\u003e \u003c/strong\u003eThe model demonstrates good calibration across the full range of predicted probabilities, with close alignment between predicted and observed frequencies, particularly at the high scores where discrimination is strongest\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"RevisedFig3validationcohortsmaller.png","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/03aa01771f569e97a22dffeb.png"},{"id":100859457,"identity":"192ea8ed-6612-4733-82f7-2d724c5ef996","added_by":"auto","created_at":"2026-01-22 07:28:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2015340,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePASS score calculator.\u003cbr\u003e\n \u003c/strong\u003eShown are screenshots of the web-based PASS calculator, showing its use for a hypothetical patient case. \u003cstrong\u003eA)\u003c/strong\u003eCalculator disclaimer\u003cstrong\u003e. B)\u003c/strong\u003eRequired clinical inputs that are typically available at the time of initial evaluation. \u003cstrong\u003eC) \u003c/strong\u003eScore components for somatic genetic testing and telomere length assessment, which may not be immediately available and are not required for calculator use; however, inclusion of these components is recommended once available to optimize diagnostic performance (see text). \u003cstrong\u003eD)\u003c/strong\u003eCalculator output displaying the total PASS score and corresponding diagnostic interpretation, along with a summary table of entered variables and assigned point values, and the distribution of PASS scores among 928 patients with bone marrow failure included in this study. The calculator is available at \u003ca href=\"https://pennmedicine.shinyapps.io/passcalc/\" target=\"_new\"\u003ehttps://pennmedicine.shinyapps.io/passcalc/\u003c/a\u003e.\u003c/p\u003e","description":"","filename":"RevisedFig4calculatorwithfig4labelsmaller.png","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/3721a4d673a42b0e57e790da.png"},{"id":100854351,"identity":"6dd09a75-81de-4b83-8125-95fe898b1cad","added_by":"auto","created_at":"2026-01-22 06:52:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2151384,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic showing the recommended use of PASS in the diagnostic evaluation of suspected acquired aplastic anemia. \u003c/strong\u003ePatients suspected of having aplastic anemia should undergo a comprehensive evaluation, as per standard guidelines. This should include evaluation of transient causes of cytopenias, and a bone marrow biopsy, with cytogenetics and molecular testing for acquired genetic alterations, and exclusion of MDS-defining abnormalities as per WHO classification criteria. We recommend PNH flow cytometry testing in all patients and find it helpful to screen for 6p LOH using cytogenomic arrays. We recommend screening for short telomeres by flow-FISH (where available), and Fanconi anemia with chromosome breakage studies (in younger adults and those anticipated to undergo bone marrow transplant). Although results of specialized testing may not be immediately available, patients can already be rapidly stratified by PASS using clinical criteria into one of three diagnostic categories: (1) high-confidence AA (PASS ≥30); (2) likely IBMFS (PASS \u0026lt;0); and (3) an intermediate group (PASS 0–20) in whom AA is likely but not certain. Patients with PASS ≥30 have ~100% predictive accuracy for AA and can proceed with AA-directed therapy without delay with no added benefit to IBMFS genetic testing; the score should be recalculated over time as additional results are received and if any new IBMFS- or AA-associated somatic features emerge. In contrast, patients with scores \u0026lt;0 should undergo comprehensive IBMFS evaluation, including genetic testing. Patients with intermediate scores have greater diagnostic uncertainty, and management should be individualized; further IBMFS testing is appropriate (particularly if transplant is planned) but in some cases, depending on disease severity, planned therapy, and access to specialized genetic diagnostics, AA-directed treatment may be initiated with appropriate patient counseling either while awaiting results or with a plan to re-evaluate in case of non-response.\u003cstrong\u003e \u003c/strong\u003eCBC, complete blood count; AA, aplastic anemia; IBMFS, inherited bone-marrow failure syndromes; HIV, human immunodeficiency virus; Hep B, hepatitis B virus; Hep C, hepatitis C virus; EBV, Epstein–Barr virus; CMV, cytomegalovirus; TSH, thyroid-stimulating hormone; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; ANA, antinuclear antibody; RF, rheumatoid factor; BM, bone marrow; T-LGL, large granular lymphocyte leukemia; FISH, fluorescence in situ hybridization; MDS, myelodysplastic syndromes; PNH, paroxysmal nocturnal hemoglobinuria; TL, telomere length; BMT, bone-marrow transplantation; 6pLOH, copy-neutral loss of heterozygosity of chromosome arm 6p; PPV, positive predictive value; HLA, human leukocyte antigen.\u003c/p\u003e","description":"","filename":"Figure5DiagnosticAlgorithmsmaller.png","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/967dd02e9ab3e9b620f55c1e.png"},{"id":107940745,"identity":"334251ac-f9a9-4ed9-b98c-7e2ae24a9400","added_by":"auto","created_at":"2026-04-27 19:49:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3411707,"visible":true,"origin":"","legend":"","description":"","filename":"PASSscoremanuscriptREVISIONVer9.12.28.2025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1_covered_acb56095-cf59-44b9-a3a5-c8e0013e68fa.pdf"},{"id":100913687,"identity":"f5a1b6e3-7ab0-4e10-b080-b8e9a96cf40d","added_by":"auto","created_at":"2026-01-22 17:44:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3621999,"visible":true,"origin":"","legend":"","description":"","filename":"456891supp886973t80psxconvrtFinalSupplement.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/38d06c68c3193ef013364d03.pdf"},{"id":100949504,"identity":"f1c50719-6e2f-438e-a308-f021113e396c","added_by":"auto","created_at":"2026-01-23 07:03:25","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3621999,"visible":true,"origin":"","legend":"Supplemental Appendix","description":"","filename":"FINALRevisedAppendixCLEANwithdatasetsforsubmission.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7725283/v1/209ce78733f87b275054c5b6.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Development and Validation of the PASS Score: A Simplified Tool to Diagnose Acquired Aplastic Anemia in Adults","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"aplastic anemia, inherited bone marrow failure, telomere, PNH, IBMFS, 6pLOH, 6p CN-LOH, BCOR, Del13q, diagnostic score, diagnosis, diagnostic tool, PASS, PASS score","lastPublishedDoi":"10.21203/rs.3.rs-7725283/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7725283/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAcquired aplastic anemia (AA) can present similarly to inherited bone marrow failure syndromes (IBMFS) but treatment differs. AA diagnosis relies on excluding IBMFS; however, genetic testing is not always available, may delay care or be inconclusive. We developed the Predictive Aplastic Score System (PASS), a clinical tool using readily available data to distinguish AA from IBMFS in adults. The training cohort included 212 adults (162 AA, 50 IBMFS). Compared to IBMFS, AA patients were older and more likely to have acute-onset, severe cytopenias. Using logistic regression with LASSO, we selected seven clinical variables for model inclusion: severity, acuity, age, IBMFS red flags, AA-associated conditions, AA-associated somatic changes, and telomere lengths. The model achieved AUC of 0.990 (95% CI: 0.982\u0026ndash;0.999), with 100% positive predictive value (PPV) for AA for scores\u0026thinsp;\u0026ge;\u0026thinsp;30. 86.8% of patients with scores\u0026thinsp;\u0026lt;\u0026thinsp;0 had IBMFS. We validated PASS in 716 patients from four external cohorts with AUC of 0.977 (95% CI: 0.968\u0026ndash;0.987). Threshold analysis confirmed 100% PPV for scores\u0026thinsp;\u0026ge;\u0026thinsp;30, rapidly diagnosing 80% of AA cases. PASS is a practical and accurate clinical tool that can rapidly distinguish AA from IBMFS for most adult patients. To promote clinical adoption, we developed open-access web calculator (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pennmedicine.shinyapps.io/passcalc/\u003c/span\u003e\u003cspan address=\"https://pennmedicine.shinyapps.io/passcalc/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e","manuscriptTitle":"Development and Validation of the PASS Score: A Simplified Tool to Diagnose Acquired Aplastic Anemia in Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-22 06:51:56","doi":"10.21203/rs.3.rs-7725283/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-01-28T18:03:46+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-17T00:54:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-14T09:42:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Leukemia","date":"2026-01-08T19:29:51+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2026-01-08T10:22:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-29T13:45:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8d6e584d-b57e-4eca-bf97-4b954a5bf3f2","owner":[],"postedDate":"January 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":61276844,"name":"Health sciences/Diseases/Haematological diseases/Anaemia"},{"id":61276845,"name":"Health sciences/Medical research/Translational research"},{"id":61276846,"name":"Health sciences/Health care/Diagnosis/Genetic testing"},{"id":61276847,"name":"Health sciences/Pathogenesis/Immunopathogenesis"},{"id":61276848,"name":"Health sciences/Signs and symptoms"}],"tags":[],"updatedAt":"2026-04-27T19:49:23+00:00","versionOfRecord":{"articleIdentity":"rs-7725283","link":"https://doi.org/10.1038/s41375-026-02924-3","journal":{"identity":"leukemia","isVorOnly":false,"title":"Leukemia"},"publishedOn":"2026-04-27 00:00:00","publishedOnDateReadable":"April 27th, 2026"},"versionCreatedAt":"2026-01-22 06:51:56","video":"","vorDoi":"10.1038/s41375-026-02924-3","vorDoiUrl":"https://doi.org/10.1038/s41375-026-02924-3","workflowStages":[]},"version":"v1","identity":"rs-7725283","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7725283","identity":"rs-7725283","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}