Among individuals with sickle cell disease and chronic pain in the Pain in Sickle Cell Epidemiology Study, those with high-impact chronic pain experienced greater pain burden, poorer physical functioning, and worse physical health.
Keywords: Pain, High-impact chronic pain, Chronic pain, Sickle cell, Health outcomes
Abstract
The US National Pain Strategy recommends identifying individuals with chronic pain (CP) who experience substantial restriction in work, social, or self-care activities as having high-impact chronic pain (HICP). High-impact chronic pain has not been examined among individuals with CP and sickle cell disease (SCD). We analyzed data from 63 individuals with SCD and CP who completed at least 5 months of pain diaries in the Pain in Sickle Cell Epidemiology Study (PiSCES). Forty-eight individuals met the definition for HICP, which was operationalized in this study as reporting pain interference on more than half of diary days. Compared with individuals without HICP, individuals with HICP experienced higher mean daily pain intensity, particularly on days without crises. They also experienced a greater proportion of days with pain, days with healthcare utilization, and days with home opioid use and higher levels of stress. They did not have a statistically significantly higher proportion of days with crises or experience higher mean daily pain intensity on days with crises. Individuals with HICP experienced worse physical functioning and worse physical health compared with those without HICP, controlling for mean pain intensity, age, sex, and education. The results of this study support that HICP is a severely affected subgroup of those with CP in SCD and is associated with greater pain burden and worse health outcomes. The findings from this study should be confirmed prospectively in a contemporary cohort of individuals with SCD.
1. Introduction
Sickle cell disease (SCD), a chronic multisystem red cell disorder affects approximately 100,000 individuals in the United States,16 and is characterized by acute painful episodes29 and chronic pain (CP).7,15,35 In the landmark Pain in Sickle Cell Epidemiology Study (PiSCES) which studied individuals aged 16 years and older, more than half had CP, and one-third of individuals had daily or near-daily pain.21,35 Chronic pain in SCD, defined as pain on most days of the month for 6 months or more,11 is associated with substantial morbidity and poor outcomes.3,4,15,31
The current definition of CP11 in SCD incorporates frequency (ie, pain on most days) and duration (ie, lasting ≥6 months) but does not consider the impact of pain on the individual. Given the heterogeneity of the impact of CP, the US National Pain Strategy report1 from the Interagency Pain Research Coordinating Committee has called for separating a severely affected group of people with CP as high-impact chronic pain (HICP), that is, those with CP who experience substantial restriction of participation in work, social, or self-care activities. Reports among nationally representative samples10,28 and among individuals with CP conditions17,43 indicate that people with HICP experience worse pain and health outcomes and healthcare care use. While recent reports demonstrate that there are subgroups or phenotypes within CP in SCD3,32 who experience worse health outcomes, there has not yet been a systematic effort to examine HICP as a CP phenotype in SCD. This represents a critical gap for the study of CP in SCD.
Among individuals with CP, those with HICP are identified as recommended by von Korff and colleagues, based on the frequency of interference with life or work activities due to pain,40 that is, a response of “most days” or “every day” when asked how often pain limits life or work activities. The domain of pain interference, which measures the impact of pain on an individual's physical, emotional, and social functioning,2 is key to understanding the impact of CP. Pain interference is adversely affected in individuals with chronic SCD pain,4,24,31 and studying pain interference may help overcome the limitations of mean pain intensity as a predictor of Health-Related Quality of Life (HRQoL) outcomes in SCD, particularly in those with daily or near-daily pain.3
In this study, we leveraged data previously collected in the landmark PiSCES study to examine the HICP phenotype in SCD. We proposed to compare the pain phenotype and outcomes between those with a HICP-like phenotype, hereafter referred to as the HICP group, with those who had CP but did not have HICP, hereafter referred to as the No-HICP group. We also examined the association between HRQoL outcomes and HICP status.
2. Methods
2.1. Study design and measures
Pain in Sickle Cell Epidemiology Study was a large prospective cohort study that enrolled individuals living with SCD aged 16 years and older from July 2002 to August 2004 in Virginia. Study design and methods have been previously published.33,35 Briefly, participants provided baseline demographic, clinical, HRQoL, and psychological data and subsequently completed daily paper pain diaries for up to 6 months reporting daily pain intensity, pain interference, medication use, and healthcare utilization. Demographic, clinical, HRQoL, and psychological data were collected at baseline. HRQoL was measured using the SF-36 composed of 8 multi-item scales42 including physical functioning (PF), role-physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role-emotional (RE), and mental health (MH),33,35 with scores for each scale ranging from 0 to 100. The SF-36 includes 2 summary measures, the physical component summary (PCS) score (physical functioning, role-physical, bodily pain, and general health) and the mental component summary (MCS) score (vitality, social functioning, role-emotional, and mental health)22,23 which were calculated as recommended. Depression, anxiety, and somatic symptom burden were measured using the PRIME-MD Patient Health Questionnaire (PHQ).38 In PiSCES, the 2 depression diagnoses generated by the PHQ (major depressive syndrome, other depressive syndrome) were combined into a single category of depression and the 2 anxiety diagnoses (panic syndrome, other anxiety syndrome) into a single category of anxiety. To measure somatic symptom burden, the PiSCES study excluded 4 items from the PHQ-15 related to common SCD pain sites to avoid measuring disease intensity instead of somatic symptom burden.36 Catastrophizing was measured using the catastrophizing subscale of the Coping Strategies Questionnaire,8 and sickle cell stress was measured by the SCD stress scale–adult.23,34 On daily paper pain diaries, participants reported the previous day's sickle cell pain intensity (“how badly I hurt”), pain interference (“how much the pain kept me from work, school, homework, family/friends”), and distress (“how upset I felt because of pain”) on a scale from 0 to 9, whether they had a pain crisis (self-defined), whether they had a visit to the emergency department (ED) or hospital, and medication use for pain.33
2.2. Study cohort
To identify a cohort with CP in PiSCES, we selected participants who had submitted pain diaries for at least 5 months (≥152.5 days) and who reported pain (ie, pain intensity >0) on >50% of reported days. This was consistent with the previous approach to identify participants with CP in PiSCES15 and the AAPT definition of CP in SCD.11
2.3. Summary measures from pain diary data
We calculated the mean, median, and 90th percentile of daily pain intensity and daily pain interference at the individual level using all available diary data. We also calculated the proportion of days with pain, defined as the proportion of days with pain intensity score >0, the proportion of days with pain interference, defined as the proportion of days with pain interference score >0, the proportion of days with pain crisis, the proportion of days with healthcare utilization for pain, and the proportion of days with home opioid use (opioid use calculated on days without healthcare utilization for pain). We also calculated mean pain intensity on days with and without crisis, as well as mean pain intensity on days with and without healthcare utilization.
2.4. High-impact chronic pain and no high-impact chronic pain subgroups
As the item used to screen for HICP40 was not collected in PiSCES, we operationalized HICP based on the frequency of pain interference on reported diary days, that is, the proportion of days with pain interference. “Most days” with pain interference was operationalized as having a pain interference score >0 on >50% of reported days.
2.5. Data analyses
We described participants' reported baseline demographic, clinical, psychological, HRQoL, and pain characteristics using means and standard deviations or frequencies and percentages, as appropriate. First, we compared differences in demographic, clinical, psychological, HRQoL, and pain characteristics between HICP and No-HICP groups using 2-sample t tests for continuous variables (or the nonparametric Kruskal–Wallis test) and the chi-square tests of independence or Fisher exact test for categorical variables. We then performed separate bivariate and multivariable linear regressions with HRQoL subscales as outcomes and the presence of HICP (binary variable) as the predictor. In multivariable models, we controlled for age, sex (male, female), education (high school or less, more than high school), and mean daily pain intensity as covariates.
All analyses were conducted in RStudio 2023.06.01 with statistical significance set at the 0.05 threshold. The Institutional Review Board at Emory University provided a nonhuman subjects' research waiver for secondary analysis of the deidentified PiSCES data set.
3. Results
3.1. Baseline characteristics
In Table 1, we report demographic, clinical, pain, psychological, and HRQoL characteristics of the full study cohort (n = 63) and by HICP status (n = 15 No-HICP, n = 48 HICP).
Table 1.
Demographic, clinical, health-related quality of life (HRQoL), psychological, and pain characteristics for analytic sample and stratified by presence or absence of high-impact chronic pain (HICP).
| Characteristics | All (n = 63) | No-HICP (n = 15) | HICP (n = 48) | P |
|---|---|---|---|---|
| Demographic and clinical | ||||
| Age (mean [SD]) | 38.22 (10.60) | 40.00 (12.09) | 37.67 (10.16) | 0.461 |
| Female (n, %) | 38 (60.3) | 9 (60.0) | 29 (60.4) | 1.000 |
| Education (n, %) | ||||
| High school or less | 24 (38.1) | 6 (40.0) | 18 (37.5) | 1.000 |
| More than high school | 39 (61.9) | 9 (60.0) | 30 (62.5) | |
| Married (n, %) | 23 (36.5) | 4 (26.7) | 19 (39.6) | 0.549 |
| Genotype (n, %) | ||||
| HbSS or HbS-β0thalassemia | 50 (79.4) | 14 (93.3) | 36 (75.0) | 0.162 |
| HbSC or S-β+thalassemia | 13 (20.6) | 1 (6.7) | 12 (25.0) | |
| Number of SCD comorbidities (median [IQR]) | 2 (1, 4) | 3 (2, 4) | 2 (1, 4) | 0.481 |
| Avascular necrosis (n, %) | 19 (30.2) | 6 (40.0) | 13 (27.1) | 0.353 |
| Skin ulcers (n, %) | 8 (12.7) | 3 (20.0) | 5 (10.4) | 0.382 |
| Pain (mean [SD]) | ||||
| Mean daily pain intensity | 4.23 (1.52) | 2.85 (0.81) | 4.66 (1.44) | <0.001 |
| Median daily pain intensity | 4.27 (1.70) | 2.73 (1.33) | 4.75 (1.51) | <0.001 |
| 90th percentile of pain intensity | 6.51 (1.68) | 5.65 (1.60) | 6.78 (1.62) | 0.021 |
| Proportion of pain days | 0.90 (0.14) | 0.78 (0.18) | 0.93 (0.10) | <0.001 |
| Mean daily pain interference | 3.17 (2.06) | 0.77 (0.67) | 3.92 (1.75) | <0.001 |
| Median daily pain interference | 2.96 (2.41) | 0.00 (0.00) | 3.89 (1.99) | <0.001 |
| 90th percentile of pain interference | 5.61 (2.71) | 2.59 (2.65) | 6.56 (1.93) | <0.001 |
| Proportion of days with pain interference | 0.71 (0.31) | 0.23 (0.16) | 0.86 (0.15) | <0.001 |
| Proportion of days with pain crisis | 0.23 (0.29) | 0.12 (0.16) | 0.26 (0.31) | 0.081 |
| Mean daily pain on days with crises | 6.04 (1.63) | 5.76 (2.10) | 6.12 (1.48) | 0.490 |
| Mean daily pain on days without crises | 3.84 (1.56) | 2.49 (0.75) | 4.27 (1.51) | <0.001 |
| Mean daily pain on days with healthcare utilization | 6.56 (1.70) | 6.65 (2.03) | 6.53 (1.63) | 0.848 |
| Mean daily pain on days without healthcare utilization | 4.11 (1.53) | 2.78 (0.81) | 4.53 (1.47) | <0.001 |
| Proportion of days with healthcare utilization for pain | 0.05 (0.07) | 0.02 (0.02) | 0.06 (0.07) | 0.048 |
| Proportion of days with home opioid use | 0.79 (0.25) | 0.65 (0.32) | 0.83 (0.22) | 0.019 |
| Psychological | ||||
| Depression (n, %) | 18 (28.6) | 4 (26.7) | 14 (29.2) | 1.000 |
| Anxiety (n, %) | 5 (7.9) | 1 (6.7) | 4 (8.3) | 1.000 |
| Catastrophizing (mean [SD]) | 13.90 (8.17) | 10.93 (8.17) | 14.91 (8.01) | 0.104 |
| Sickle cell stress (mean [SD]) | 21.51 (9.34) | 16.20 (9.53) | 23.17 (8.74) | 0.011 |
| Coping (mean [SD]) | ||||
| Affective or emotional focused | 2.92 (1.06) | 2.58 (0.85) | 3.02 (1.11) | 0.161 |
| Passive or behavioral adherence | 4.11 (0.93) | 3.93 (0.64) | 4.17 (1.01) | 0.405 |
| Active | 2.90 (1.21) | 2.52 (1.30) | 3.02 (1.17) | 0.164 |
| Somatic symptom score (mean [SD]) | 8.27 (4.01) | 6.53 (3.42) | 8.81 (4.06) | 0.054 |
| HRQoL (mean [SD]) | ||||
| General health (GH) | 31.19 (17.67) | 35.33 (15.98) | 29.84 (18.14) | 0.299 |
| Physical functioning (PF) | 53.84 (22.56) | 66.59 (21.87) | 49.85 (21.46) | 0.011 |
| Mental health (MH) | 73.27 (16.84) | 80.27 (14.38) | 71.04 (17.09) | 0.064 |
| Social functioning (SF) | 60.32 (24.65) | 71.67 (26.08) | 56.77 (23.34) | 0.040 |
| Bodily pain (BP) | 37.94 (20.31) | 47.33 (21.18) | 34.95 (19.30) | 0.039 |
| Vitality (VT) | 39.97 (21.71) | 45.33 (19.32) | 38.26 (22.34) | 0.276 |
| Role-physical (RP) | 28.69 (37.03) | 51.67 (39.49) | 21.20 (33.32) | 0.005 |
| Role-emotional (RE) | 51.37 (44.13) | 71.11 (37.52) | 44.93 (44.57) | 0.045 |
| Physical component summary score (PCS) | 30.80 (8.37) | 35.00 (8.39) | 29.49 (8.00) | 0.025 |
| Mental component summary score (MCS) | 47.41 (10.05) | 51.25 (9.34) | 46.21 (10.05) | 0.091 |
Compared using t tests with equal variances (or the Kruskal–Wallis test) for continuous variables and chi-square tests of independence with Yates continuity correction or Fisher exact test for categorical variables. Note: n = 59 to 63 (psychological variables) and 61 to 63 (HRQoL variables).
Statistically significant values were highlighted in bold.
There were no differences in demographic and clinical characteristics between HICP and No-HICP individuals. We found that the mean, median, and 90th percentile of daily pain intensity and daily pain interference, as well as the proportion of pain days and proportion of days with pain interference, was significantly higher in individuals with HICP. Individuals with HICP also reported higher mean pain on days without crisis and days without healthcare utilization, a greater proportion of days with healthcare utilization for pain, and a greater proportion of days with home opioid use. There were however no statistically significant differences between the HICP and no-HICP groups in mean daily pain intensity on days with crisis or days with healthcare utilization. Sickle cell stress was significantly higher in participants with HICP while depression, anxiety, and other psychological characteristics were not statistically different between the 2 groups. Finally, those with HICP had worse overall physical health as measured by the PCS score and poorer scores for the PF, SF, BP, RP, and RE subscales. Figure 1 represents higher mean daily pain interference levels and lower PF scores among those with HICP compared with the No-HICP subgroup.
Figure 1.
Cumulative proportion of individuals with sickle cell disease and chronic pain with mean daily pain interference (Panel A) and physical functioning (Panel B) at indicated level or lower; comparison of distributions between high-impact chronic pain (high-impact chronic pain, n = 48) and no high-impact chronic pain (n = 15) groups.
3.2. High-impact chronic pain status and health-related quality of life outcomes
As reported in Table 2, there were statistically significant negative associations between the presence of HICP and most HRQoL outcomes in the bivariable models. After controlling for age, sex, education, and mean daily pain intensity, only associations with physical health–related subscales, that is, PF (No-HICP LS-Mean: 67.7 vs HICP LS-Mean: 52.0, P = 0.024), RP (No-HICP LS-Mean: 55.6 vs HICP LS-Mean: 24.2, P = 0.011), and PCS score (No-HICP LS-Mean: 35.9 vs HICP LS-Mean: 30.5, P = 0.038) outcomes remained statistically significant. In these models, sex was a statistically significant independent (nonspecific) predictor of HRQoL outcomes except for SF and RP subscales.
Table 2.
Association between high-impact chronic pain (HICP) and health-related quality of life (HRQoL), least-square (LS-means) with 95% confidence intervals (CI), and P-values (P) are reported.
| HRQoL components | Unadjusted | Adjusted* | ||
|---|---|---|---|---|
| LS-means (95% CI) | P | LS-means (95% CI) | P | |
| General health | 0.299 | 0.712 | ||
| No-HICP | 35.3 (26.2-44.5) | 35.0 (25.8-44.3) | ||
| HICP | 29.8 (24.6-35.0) | 33.0 (27.9-38.1) | ||
| Physical functioning | 0.011 | 0.024 | ||
| No-HICP | 66.6 (55.5-77.7) | 67.7 (56.1-79.2) | ||
| HICP | 49.8 (43.6-56.1) | 52.0 (45.8-58.1) | ||
| Mental health | 0.064 | 0.384 | ||
| No-HICP | 80.3 (71.7-88.8) | 78.0 (68.8-87.2) | ||
| HICP | 71.0 (66.2-75.9) | 73.2 (68.3-78.1) | ||
| Social functioning | 0.040 | 0.313 | ||
| No-HICP | 71.7 (59.3-84.1) | 68.9 (55.4-82.5) | ||
| HICP | 56.8 (49.8-63.7) | 60.8 (53.6-68.0) | ||
| Bodily pain | 0.039 | 0.281 | ||
| No-HICP | 47.3 (37.1-57.5) | 45.1 (34.4-55.8) | ||
| HICP | 34.9 (29.2-40.7) | 38.3 (32.5-44.0) | ||
| Vitality | 0.276 | 0.156 | ||
| No-HICP | 45.3 (34.1-56.5) | 49.6 (38.4-60.9) | ||
| HICP | 38.3 (31.9-44.6) | 40.1 (34.1-46.1) | ||
| Role-physical | 0.005 | 0.011 | ||
| No-HICP | 51.7 (33.6-69.7) | 55.6 (35.4-75.8) | ||
| HICP | 21.2 (10.9-31.5) | 24.2 (13.1-35.2) | ||
| Role-emotional | 0.045 | 0.097 | ||
| No-HICP | 71.1 (48.9-93.3) | 71.5 (47.3-95.7) | ||
| HICP | 44.9 (32.2-57.6) | 47.4 (34.2-60.6) | ||
| Physical component summary score | 0.025 | 0.038 | ||
| No-HICP | 35.0 (30.8-39.2) | 35.9 (31.6-40.3) | ||
| HICP | 29.5 (27.2-31.8) | 30.5 (28.2-32.8) | ||
| Mental component summary score | 0.091 | 0.313 | ||
| No-HICP | 51.2 (46.1-56.4) | 50.7 (45.1-56.3) | ||
| HICP | 46.2 (43.4-49.1) | 47.4 (44.4-50.3) | ||
Unadjusted models and models adjusted for clinical covariates are shown.
Adjusted models adjusted for age, sex, education, and mean daily pain intensity n = 61 to 63.
Statistically significant values were highlighted in bold.
4. Discussion
In this study, we built on previous observations from PiSCES and provide empirical evidence to support the heterogeneity of the CP phenotype in SCD and the stratification of CP based on the frequency of pain interference, that is, the presence of HICP, to identify a severely affected subgroup of CP that experienced greater pain burden and worse health outcomes.
Overall, the results of this study indicate that those with HICP experience a greater burden of pain. Individuals with HICP in this cohort experienced higher mean daily pain intensity overall and on days without crises or healthcare utilization. They also experienced more healthcare utilization and home opioid use. They did not, however, experience higher mean daily pain intensity on days with crises, suggesting that both groups appear to experience similar severe pain during a self-reported crisis. Similarly, the relatively high levels of mean daily pain intensity on days with healthcare utilization and the lack of differences between groups demonstrates that individuals with CP and SCD, regardless of their CP phenotype, tend to seek ED or hospital care during periods of severe pain.
In this study, we found that participants with HICP have worse physical health as compared with those without HICP. While we demonstrated worse HRQoL outcomes in HICP in multiple domains in unadjusted models, in models adjusted for mean daily pain intensity and sociodemographic variables, only the association with PF (and related physical health scales) remained statistically significant. This also highlights the complex relationship between CP and outcomes and the importance of accounting for mean daily pain intensity and sociodemographic covariates when studying associations between CP phenotypes and HRQoL outcomes. Overall, the findings of this study align with previous reports from the National Health Interview Survey and observations from other CP conditions,17,18,28,41,43 which indicate that individuals with HICP have more pain, higher healthcare use, and worse HRQoL. These results continue to support the inclusion of pain interference as an outcome in the evaluation of interventions for CP in SCD, consistent with the IMMPACT recommendations to measure pain interference as a core outcome in clinical trials of CP12 and the current therapeutic approach to CP12,13,27 and CP in SCD.6
We found that participants with HICP had significantly higher stress scores, using a scale specifically designed to capture sickle cell–related stress.34 This is consistent with the published role of stress in CP in disorders other than SCD.37 Unlike previous observations,14,28 we did not find a significant difference between the HICP and No-HICP groups in psychological characteristics or MH subscale scores. This may have been related to the small sample size in this study. Given the known associations of psychological comorbidities with HICP,14,28 this should be examined in larger prospective studies of HICP in SCD.
To our knowledge, this is the first examination of HICP in SCD using data previously collected in PiSCES, but the study has several limitations. We operationalized the definition of HICP to identify those with a HICP-like phenotype in this cohort, and participants were not prospectively screened for HICP using current recommendations. The sample size was limited, and 76 percent of this cohort had a HICP phenotype, which while consistent with other observational studies of HICP in non-SCD populations30,43 was much higher than the population prevalence estimates from the NHIS,25,28 suggesting the possibility of a sampling bias. The PiSCES study collected data between 2002 and 2004; comprehensive SCD care has since expanded, and there is increased use of disease-modifying therapies such as hydroxyurea. Therefore, the associations observed in this cohort must be confirmed by examination in larger contemporary cohorts of individuals with SCD and CP. Daily pain interference and intensity data were collected in PiSCES using paper pain diaries, which are subject to errors, backfilling, and poor compliance.3,5,20,26,39 Our analysis was limited to the SF-36 HRQoL outcomes collected in PiSCES before the introduction of the Patient Reported Outcomes Measurement Information System (PROMIS) measurement protocols and SCD-specific patient-reported outcome measures such as the Adult Sickle Cell Quality of Life Measurement System (ASCQ-ME),9,19 and future studies should incorporate these measures. Future studies of CP and HICP should also examine the role of contributors of CP that are specific to SCD, for example, avascular necrosis and leg ulcers. Finally, although this study expands our understanding of the impact of pain on HRQoL outcomes in SCD, the cross-sectional nature of the health outcomes collected prevents us from making any longitudinal associations and causal conclusions.
5. Conclusion
Among individuals with SCD and CP in PiSCES, those with HICP experienced greater pain burden, poorer physical functioning, and worse physical health. The findings from this study should be confirmed prospectively in a contemporary cohort of individuals with SCD.
Conflict of interest statement
The authors have no conflicts of interest to declare.
Acknowledgements
This study was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number R03HL162694 to Nitya Bakshi. Nitya Bakshi also received funding from the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K23HL140142 and K23HL140142−03S1. Nitya Bakshi also received funding from the Program for Retaining, Supporting, and EleVating Early-career Researchers at Emory (PeRSEVERE) from the Emory School of Medicine, a gift from the Doris Duke Charitable Foundation COVID 19 Fund to Retain Clinical Scientists, and through the Georgia Clinical and Translational Science Alliance under award UL1-TR002378. The Pain in Sickle Cell Epidemiology Study was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number R01HL064122 to Wally R. Smith. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Data availability statement: Data available from authors upon reasonable request.
Footnotes
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
Contributor Information
Ashna Jagtiani, Email: ashna.jagtiani@emory.edu.
Eric Chou, Email: echou53@gmail.com.
Scott E. Gillespie, Email: scott.gillespie@emory.edu.
Katie Liu, Email: katie.liu@emory.edu.
Lakshmanan Krishnamurti, Email: lakshmanan.krishnamurti@yale.edu.
Donna McClish, Email: donna.mcclish@gmail.com.
Wally R. Smith, Email: wally.smith@vcuhealth.org.
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