Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry.
Sickle cell disease (SCD) affects millions of individuals worldwide, and is characterized by both acute, episodic pain and chronic, persistent pain. Despite the significant burden of the disease, clinicians continue to face significant challenges in treating SCD pain due to variability in pain exper...
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0320889 |
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| author | Martha O Kenney Samuel Wilson Morgan Rosser Sophie Lanzkron Julie Kanter Susan Padrino Payal Desai Deepa Manwani Alice Cohen Stephanie Guarino Ward Hagar Joshua Field Jane Little |
| author_facet | Martha O Kenney Samuel Wilson Morgan Rosser Sophie Lanzkron Julie Kanter Susan Padrino Payal Desai Deepa Manwani Alice Cohen Stephanie Guarino Ward Hagar Joshua Field Jane Little |
| author_sort | Martha O Kenney |
| collection | DOAJ |
| description | Sickle cell disease (SCD) affects millions of individuals worldwide, and is characterized by both acute, episodic pain and chronic, persistent pain. Despite the significant burden of the disease, clinicians continue to face significant challenges in treating SCD pain due to variability in pain experiences. The objectives of this study were (1) to identify distinct pain subgroups based on demographic and biopsychosocial characteristics and (2) to evaluate the relationship between the subgroups and pain impact - a SCD-disease specific measure of pain interference. To achieve these objectives, we performed a hierarchical cluster analysis on a cross-sectional sample of adults with SCD who are enrolled in the Globin Research Network Data and Discovery (GRNDaD) registry. Five hundred thirty-two participants (61% females and 64% with chronic pain) were included in the analysis. Six distinct subgroups were identified, 3 with chronic pain (Clusters 1-3) and 3 without chronic pain (Clusters 4-6). Despite differences in biological markers of disease severity such as genotype, hemoglobin and fetal hemoglobin percentage, chronic pain subgroups had comparable odds of reporting worse pain impact, suggesting that chronic pain has a disproportionate influence on SCD pain when compared to other factors. Longitudinal studies are needed to further validate these findings and to determine how these pain subgroups may change. Overall, our findings indicate that understanding and preventing chronic pain in SCD must be a top priority to improve the quality of life of those living with SCD. |
| format | Article |
| id | doaj-art-6fc2f04bd5bc449bb38b063441c1248c |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS ONE |
| spelling | doaj-art-6fc2f04bd5bc449bb38b063441c1248c2025-08-20T03:25:52ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e032088910.1371/journal.pone.0320889Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry.Martha O KenneySamuel WilsonMorgan RosserSophie LanzkronJulie KanterSusan PadrinoPayal DesaiDeepa ManwaniAlice CohenStephanie GuarinoWard HagarJoshua FieldJane LittleSickle cell disease (SCD) affects millions of individuals worldwide, and is characterized by both acute, episodic pain and chronic, persistent pain. Despite the significant burden of the disease, clinicians continue to face significant challenges in treating SCD pain due to variability in pain experiences. The objectives of this study were (1) to identify distinct pain subgroups based on demographic and biopsychosocial characteristics and (2) to evaluate the relationship between the subgroups and pain impact - a SCD-disease specific measure of pain interference. To achieve these objectives, we performed a hierarchical cluster analysis on a cross-sectional sample of adults with SCD who are enrolled in the Globin Research Network Data and Discovery (GRNDaD) registry. Five hundred thirty-two participants (61% females and 64% with chronic pain) were included in the analysis. Six distinct subgroups were identified, 3 with chronic pain (Clusters 1-3) and 3 without chronic pain (Clusters 4-6). Despite differences in biological markers of disease severity such as genotype, hemoglobin and fetal hemoglobin percentage, chronic pain subgroups had comparable odds of reporting worse pain impact, suggesting that chronic pain has a disproportionate influence on SCD pain when compared to other factors. Longitudinal studies are needed to further validate these findings and to determine how these pain subgroups may change. Overall, our findings indicate that understanding and preventing chronic pain in SCD must be a top priority to improve the quality of life of those living with SCD.https://doi.org/10.1371/journal.pone.0320889 |
| spellingShingle | Martha O Kenney Samuel Wilson Morgan Rosser Sophie Lanzkron Julie Kanter Susan Padrino Payal Desai Deepa Manwani Alice Cohen Stephanie Guarino Ward Hagar Joshua Field Jane Little Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry. PLoS ONE |
| title | Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry. |
| title_full | Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry. |
| title_fullStr | Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry. |
| title_full_unstemmed | Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry. |
| title_short | Identifying distinct subgroups with severe pain in sickle cell disease: A cluster analysis of the GRNDaD multi-center registry. |
| title_sort | identifying distinct subgroups with severe pain in sickle cell disease a cluster analysis of the grndad multi center registry |
| url | https://doi.org/10.1371/journal.pone.0320889 |
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