Systematic review of acupuncture to control hot flashes in cancer patients

Hot flashes (HFs) are a common side effect of cancer treatment. The purpose of this systematic review was to evaluate evidence related to the use of acupuncture for HFs in cancer patients. EMBASE, MEDLINE, Cochrane (all databases), PubMed, the Cumulative Index to Nursing and Allied Health Literature, and Scopus were searched from their inception through December 2014. Included studies had to be randomized controlled trials with a usual-care and/or placebo comparison group that investigated acupuncture to treat HFs in cancer patients. No language limits were applied. The risk of bias (ROB) was rated as low, high, or unclear according to Cochrane criteria. Both within-group and between-group changes were evaluated. Four hundred two items were identified, and 192 duplicates were omitted; this left 210 publications to be screened. Eight studies met the inclusion criteria, and all involved women with breast cancer. All studies showed significant within-group improvement from the baseline for true acupuncture (TA). One study showed significant improvement in favor of TA over sham acupuncture (SA; P < .001), 1 study found in favor of TA over SA for nighttime HFs only (P = .03), and 1 study found in favor of TA over SA or untreated controls (P < .01 and P < .001, respectively). Between-group (TA vs SA) effect size (ES) estimates for daytime and nighttime HFs were calculated (ES range, 0.04-0.9) whenever possible. No studies were rated with a low ROB. In conclusion, the current level of evidence is insufficient to either support or refute the benefits of acupuncture for the management of HFs in cancer patients. Future studies should provide within-group and between-group ES estimates in addition to P values. Cancer 2015;121:3948-3958. (c) 2015 American Cancer Society. The current level of evidence is insufficient to either support or refute the benefits of acupuncture for the management of hot flashes in cancer patients. Future studies should provide within-group and between-group effect size estimates in addition to P values.