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X Demographics
Mendeley readers
| Title |
Illustrating risk difference and number needed to treat from a randomized controlled trial of spinal manipulation for cervicogenic headache
|
|---|---|
| Published in |
Chiropractic & Manual Therapies, May 2010
|
| DOI | 10.1186/1746-1340-18-9 |
| Pubmed ID | |
| Authors |
Mitchell Haas, Michael Schneider, Darcy Vavrek |
| Abstract |
The number needed to treat (NNT) for one participant to benefit is considered a useful, clinically meaningful way of reporting binary outcomes from randomized trials. Analysis of continuous data from our randomized controlled trial has previously demonstrated a significant and clinically important difference favoring spinal manipulation over a light massage control. Eighty participants were randomized to receive spinal manipulation or a light massage control (n = 40/group). Improvements in cervicogenic headache pain (primary outcome), disability, and number in prior four weeks were dichotomized into binary outcomes at two thresholds: 30% representing minimal clinically important change and 50% representing clinical success. Groups were compared at 12 and 24-week follow-up using binomial regression (generalized linear models) to compute the adjusted risk difference (RD) between groups and number needed to treat (NNT) after adjusting for baseline differences between groups. Results were compared to logistic regression results. For headache pain, clinically important improvement (30% or 50%) was more likely for spinal manipulation: adjusted RD = 17% to 27% and NNT = 3.8 to 5.8 (p = .005 to .028). Some statistically significant results favoring manipulation were found for headache disability and number. Spinal manipulation demonstrated a benefit in terms of a clinically important improvement of cervicogenic headache pain. The use of adjusted NNT is recommended; however, adjusted RD may be easier to interpret than NNT. The study demonstrated how results may depend on the threshold for dichotomizing variables into binary outcomes. ClinicalTrials.gov NLM identifier NCT00246350. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 1 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| France | 1 | 1% |
| Unknown | 95 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 20% |
| Researcher | 13 | 13% |
| Student > Bachelor | 12 | 12% |
| Student > Doctoral Student | 7 | 7% |
| Other | 7 | 7% |
| Other | 27 | 28% |
| Unknown | 12 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 47 | 48% |
| Nursing and Health Professions | 23 | 24% |
| Agricultural and Biological Sciences | 2 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Computer Science | 1 | 1% |
| Other | 6 | 6% |
| Unknown | 17 | 18% |