- Design
- Systematic review and network meta-analysis of randomised trials
- Population
- 12 RCTs, 736 patients receiving chemotherapy
- Primary outcome
- Hair preservation as defined by each trial
- Effect
- Prolonged scalp cooling vs usual care RR 24.66 (95% CI 7.07 to 86.05); low certainty
A registered network meta-analysis included 12 randomised trials of 736 patients comparing nine strategies to prevent chemotherapy-induced hair loss: scalp cooling for short (up to 45 minutes), traditional (46 to 90 minutes) or prolonged (over 90 minutes) periods after chemotherapy, scalp compression, four drugs, and usual care.
Prolonged scalp cooling ranked highest and preserved hair far more often than usual care (risk ratio 24.7, 95% CI 7.1 to 86.1) and somewhat more than traditional cooling (RR 2.1). It did not differ significantly from short-duration cooling (RR 2.1, 95% CI 0.8 to 5.4).
Most trials carried a high risk of bias and certainty was low to very low. Hair preservation was defined differently across trials, and the very wide intervals reflect small numbers.
For dermatologists asked about hair loss before chemotherapy, scalp cooling is the option with evidence behind it. Availability in Indian oncology units is variable, and whether it suits a given regimen is a decision for the oncology team.
- Raise scalp cooling with patients before chemotherapy starts, when it can still be arranged.
- Longer cooling after each infusion may help more, but the evidence is low certainty.
- No drug in this analysis matched scalp cooling for preserving hair.
- Check availability and regimen suitability with the treating oncology team.
Why it matters
Hair loss is one of the most feared effects of chemotherapy, and the length of cooling may matter as much as whether it is used.
Don't overread it
The certainty of evidence was low to very low, and prolonged cooling did not significantly beat short cooling.
The statistics, in plain English
A risk ratio of 24.7 with an interval from 7 to 86 means the effect is large but very imprecise. Network meta-analysis compares treatments indirectly through shared comparators, and rankings can shift when trials are small and biased, as here.
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