Question · asked by 1 review

MSCs vs placebo or control: Death during study period

MSCs showed no clear difference in all‐cause mortality (prophylactic trials) (over duration of trial) compared with control/placebo (low certainty).

What each review found

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FindingEffectStudiesGRADE certainty
MSCs vs control/placebo
All‐cause mortality (prophylactic trials) (over duration of trial) · patients with a haematological condition who receive a haematopoietic stem cell transplant as treatment for their…
MSCs showed no clear difference in all‐cause mortality (prophylactic trials) (over duration of trial) compared with control/placebo (low certainty).
Mesenchymal stromal cells as treatment or prophylaxis for acute or chronic graft‐versus‐host disease in… (2019) · Cochrane Headline outcomes only
HR 0.85 [0.5, 1.42]5 studies · 301 participantsLow
MSCs vs control/placebo
All‐cause mortality (therapeutic trials) (over duration of trial) · patients with a haematological condition who receive a haematopoietic stem cell transplant as treatment for their…
It is very uncertain whether MSCs changes all‐cause mortality (therapeutic trials) (over duration of trial) compared with control/placebo (very low certainty).
Mesenchymal stromal cells as treatment or prophylaxis for acute or chronic graft‐versus‐host disease in… (2019) · Cochrane Headline outcomes only
HR 1.12 [0.8, 1.56]1 study · 244 participantsVery low

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Mesenchymal stromal cells as treatment or prophylaxis for acute or chronic graft‐versus‐host disease in haematopoietic stem cell…
2019 · Cochrane Headline outcomes only
Not reportedlist not extracted yetNot assessed

Studies behind the findings

None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.