Complementary and Alternative Medicine (CAM) Use Reported Among Individuals with Immune Thrombocytopenia (ITP): Data from the ITP Natural History Study Registry
Bibliographic record
Abstract
Background and Aims: CAM refers to non-traditional disease treatments, like supplements and dietary modifications, used either alone or alongside conventional medicine. The use of CAM in children and adults with immune thrombocytopenia (ITP), an autoimmune bleeding disorder, has not been well-studied or reported. Patients may be reluctant to share CAM use with health care providers (HCPs). Here, we describe the prevalence, associated characteristics, and reporting of CAM use among individuals with ITP based on survey data collected from the ITP Natural History Study Registry. Methods: This is a prospective cohort study of self-reporting adults and caregivers of children with thrombocytopenia registered in the ITP Natural History Study Registry. Data were collected between February 2017-May 2024; from the following surveys: participant profile, diagnosis, treatment, COVID-19 (for non-COVID related recent treatment history only), and bleeding and hospitalization. Participants were included if they entered data for all five surveys. Data were analyzed with descriptive statistics, two-tailed T-tests, and chi-square analysis. Results: A total of 788 participants were included. Most were female (74%) and had primary (82%) and chronic ITP (78%). The median age at the time of ITP diagnosis was 33 years (range 1-85). The median age of survey completion was 51 years; age of participants ranged from <18 years (6%, 49/788) to 18-59 (62%, 492/788) to >60 (31%, 247/788). Most individuals live in the US (79%); other countries included Canada (9%), UK (4%), and Australia (3%). An additional 5% were from other countries. The majority had health insurance (94%; 729/788), and 27% (210/788) reported currently receiving treatment for their ITP. Of the 788 participants, half (49%, 389/788) reported using both traditional therapies and CAM, 44% (348/788) reported using traditional therapies without CAM, and 6% (51/788) had never used either CAM or traditional therapies. Only 23% had discussed CAM use with their HCP. CAM users were more likely to see a naturopathic/holistic provider for their ITP management (27%) compared to non-CAM users (5%) (p = 0.011). Dietary modifications were reported by 73 (9%) participants including gluten-free, vegan, macrobiotic, anti-quinine, anti-inflammatory, anti-aspartame, anti-caffeine and anti-alcohol diets. The most common diets reported were gluten free (45%; 33/73) and anti-inflammatory (44%; 32/73). Supplements were reported in 389 participants, although the specific supplement was reported by only 87 participants and included melatonin, folic acid, papaya leaf extract, coenzyme Q10, chlorophyll, and vitamins C, D, K, and B12. Vitamin D was the predominant supplement (90%; 78/87) used. Among CAM users, 10% reported using a CAM within the first year of their ITP diagnosis; 30% within the first 5 years, and 53% within the first 9 years. Despite the frequent use of CAM, when asked specifically about current or previous treatment for ITP, the majority did not select that they had used a CAM (98%, 634/646). CAM users tended to be older at ITP diagnosis (median age 36 years vs. 29 years, p = 0.0039) and survey completion (median age 53 years vs. 38 years, p = 0.00016) than non-CAM users and were more likely to be between the ages of 50-69 years (57%, 160/279, p = 0.0011) compared to non-CAM users. CAM users had a higher median number of prior traditional treatments (2 vs 1, p = <0.0001), and reported a higher education (college, university, or graduate studies) compared to those using traditional medication only (p<0.00001). There was no difference in CAM use by country, race, health insurance, income level, employment, or hospitalization frequency. Conclusion: CAM use was common among respondents particularly among older adults and those with a higher level of education. Half reported using either a supplement or dietary modification to treat their ITP although only 23% reported discussing CAM use with their HCP. HCPs should inquire about CAM use and specifically ask about supplements and/or dietary modifications as the term ‘CAM’ may not be understood, as shown here. Discussing CAM use with patients is important for evaluating drug-interactions with traditional therapies and the effect these interventions may have on ITP. Further studies should investigate the prevalence of CAM use in a wider ITP patient population and describe the reasons for, perceptions of, and types of CAM use in ITP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".