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. 2020 Oct 28:12:625-633.
doi: 10.2147/CEOR.S276121. eCollection 2020.

Development of a Severity Classification System for Sickle Cell Disease

Affiliations

Development of a Severity Classification System for Sickle Cell Disease

Nirmish Shah et al. Clinicoecon Outcomes Res. .

Abstract

Purpose: There is no well-accepted classification system of overall sickle cell disease (SCD) severity. We sought to develop a system that could be tested as a clinical outcome predictor.

Patients and methods: Using validated methodology (RAND/UCLA modified Delphi panel), 10 multi-disciplinary expert clinicians collaboratively developed 180 simplified patient histories and rated each on multiple axes (estimated clinician follow-up frequency, risk of complications or death, quality of life, overall disease severity). Using ratings on overall disease severity, we developed a 3-level severity classification system ranging from Class I (least severe) to Class III (most severe).

Results: The system defines patients as Class I who are 8-40 years with no end organ damage, no chronic pain, and ≤4 unscheduled acute care visits due to vaso-occlusive crises (VOC) in the last year. Patients <8 or >40 years with no end organ damage, no chronic pain, and <2 unscheduled acute care visits are also considered Class I. Patients any age with ≥5 unscheduled acute care visits and/or with severe damage to bone, retina, heart, lung, kidney, or brain are classified as Class III (except patients ≥25 years with severe retinopathy, no chronic pain, and 0-1 unscheduled acute care visits, who are considered Class II). Patients not meeting these Class I or III definitions are classified as Class II.

Conclusion: This system consolidates patient characteristics into homogenous groups with respect to disease state to support clinical decision-making. The system is consistent with existing literature that increased unscheduled acute care visits and organ damage translate into clinically significant patient morbidity. Studies to further validate this system are planned.

Keywords: chronic pain; disease severity; expert panel; organ damage; vaso-occlusive crises.

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Conflict of interest statement

Nirmish Shah has received funding from Novartis (honoraria, consultancy, research funding, speaker’s bureau), Alexion (speaker’s bureau), Global Blood Therapeutics (research funding), CSL Behring and Bluebird Bio (consultant). David Beenhouwer, Michael Broder, Sarah N Gibbs, and Irina Yermilov are employees of the Partnership for Health Analytic Research (PHAR), LLC, which was paid by Novartis to conduct the research described in this manuscript. David Beenhouwer, Michael Broder, Sarah N Gibbs, and Irina Yermilov are employees of the Partnership for Health Analytic Research (PHAR), LLC, which was paid by AbbVie, Akcea, ASPC, Amgen, AstraZeneca, BMS, Boston Scientific Corporation, Celgene, Eisai, Ethicon, GRAIL, Helsinn, Illumina, Innovation and Value Initiative, Ionis, Jazz, Kite, Novartis, Otsuka, Pathnostics, PhRMA, Prothena, Sage, Verde Technologies, Genentech, Greenwich Biosciences, Mirum Pharmaceuticals, Sanofi US Services, Sunovion Pharmaceuticals, and Dompe US to conduct research outside of the submitted work. Lanetta Bronte-Hall has received funding from Novartis (honoraria, consulting), Global Blood Therapeutics (research funding), Pfizer (consultancy and research support), and BlueBird Bio (research funding). Laura M De Castro has received funding from Novartis (honoraria, membership on Board of Directors or advisory committees), Global Blood Therapeutics (membership on Board of Directors or advisory committees), and Pfizer (consultancy). She has received research support from Global Blood Therapeutics, Novartis, Pfizer, and Bayer. Victor Gordeuk has received funding from Global Blood Therapeutics (honoraria, consultancy, research funding), Emmaus (honoraria, consultancy), Novartis (honoraria, consultancy, research funding), Modus Therapeutics (honoraria, consultancy), Pfizer (research funding), Inctye (research funding), CSL Behring (honoraria, consultancy, research funding), Ironwood (research funding), and Imara (research funding). Julie Kanter has received funding from Novartis (honoraria, membership on advisory committees). She has also received funding from AstraZeneca (steering committee), Imara (honoraria), Modus Therapeutics (honoraria), and Global Blood Therapeutics (travel). Elizabeth S Klings has received funding from Novartis (honoraria). She has received research support from Actelion, Reata, Incyte, Bayer, Arena/United Therapeutics. She has received funding from Pfizer (membership on Acute Chest Syndrome adjudication committee for Rivipansel clinical trial) and Micelle (Data and Safety Monitoring Board). Thokozeni Lipato has received funding from Novartis (honoraria) and Global Blood Therapeutics (speaker’s bureau). Deepa Manwani has received funding from Novartis (honoraria, consultancy), Pfizer (consultancy), and Global Blood Therapeutics (consultancy, research funding). Brigid Scullin has received funding from Novartis (honoraria, consultancy). Wally R Smith has received funding from Novartis (honoraria, consultancy) and reports funding as an investigator for NHLBI, HRSA, PCORI, Pfizer, Novartis, Emmaus, Imara, and Shire; consultant for Novartis, Pfizer, Global Blood Therapeutics, and Emmaus. The authors report no other conflicts of interest in this work. Selected components of this work were presented at the 2019 American Society of Hematology (ASH) Annual Meeting in Orlando, Florida, on December 8, 2019.

Figures

Figure 1
Figure 1
Example rating form of patient scenarios. Each cell represents 1 patient scenario. The table is read from top to bottom and left to right. For example, the first cell in column A1 reads: “In a patient with no end organ damage, no chronic pain, 0–1 unscheduled acute care visits due to VOCs in the last year, with HbSS or HbSβ0, how often should this patient be seen by a SCD provider?” aThis table was replicated for each patient age group: Patient <8, 8–15 years old, 25–40 years old, >40 years old. Young children might have no history, so the classification system might not be as applicable. bA SCD provider includes any clinician treating SCD and its primary consequences (eg, hematologist or pulmonologist). cAdditional serious complications include end organ damage, sepsis, or other. dRisk of complications or death in the next 5 years for patients ≥16 years old and next 10 years for patients <16 years old. eChronic pain defined as ongoing pain present on most days over the past 6 months. fAcute care includes unscheduled office visits, ED visits, day hospital visits, and hospitalizations; VOCs include pain, priapism, acute chest syndrome, splenic sequestration, and hepatic sequestration. gRefer to Table 1 for definitions of end organ damage provided.
Figure 2
Figure 2
Expert agreement on overall disease severity classifications. Each cell represents 1 patient scenario. Class levels are color coded: The lightest blue represents Class I (least severe disease) and the darkest blue represents Class III (most severe disease).
Figure 3
Figure 3
Patient classification flow chart. Class I represents least severe disease and Class III represents most severe disease. aPatients ≥25 years old presenting with severe retinopathy, no chronic pain, and <2 unscheduled acute care visits due to VOCs in the last year are Class II.

References

    1. Quinn CT. Minireview: clinical severity in sickle cell disease: the challenges of definition and prognostication. Exp Biol Med. 2016;241(7):679–688. doi:10.1177/1535370216640385 - DOI - PMC - PubMed
    1. Miller ST, Sleeper LA, Pegelow CH, et al. Prediction of adverse outcomes in children with sickle cell disease. N Engl J Med. 2000;342(2):83–89. doi:10.1056/NEJM200001133420203 - DOI - PubMed
    1. Day SW. Development and evaluation of a sickle cell disease assessment instrument. Pediatr Nurs. 2004;30(6). - PubMed
    1. Sebastiani P, Nolan VG, Baldwin CT, et al. A network model to predict the risk of death in sickle cell disease. Blood. 2007;110(7):2727–2735. doi:10.1182/blood-2007-04-084921 - DOI - PMC - PubMed
    1. van den Tweel XW, van der Lee JH, Heijboer H, Peters M, Fijnvandraat K. Development and validation of a pediatric severity index for sickle cell patients. Am J Hematol. 2010;85(10):746–751. doi:10.1002/ajh.21846 - DOI - PubMed

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