Review Article

Real-World Evidence of Traditional Chinese Medicine (TCM) Treatment on Cancer: A Literature-Based Review

Table 1

The distinction between real-world study and randomized controlled trials, cohort studies, and case reports.

CharacteristicRandomized controlled trials (RCT)Real-world study (RCT)Cohort studyCase-control study

PurposeFocused on efficacyDiverse research purposes, including efficacy studiesTest etiological hypotheses, evaluate preventive effects, and study the natural history of diseaseExplore the cause of disease

Study populationIdeal world crowd and strict standards of inclusion and exclusionReal-world population and broader inclusion and exclusion criteriaExposure to study factors and control groupsPeople with and without the disease

Sample sizeCalculated according to statistical formula, the sample size is limitedCalculated based on the real world or statistical formula, the sample size can be large or smallCalculated according to statistical formula, the sample size is required to be largeCalculated based on the study design or statistical formula, the sample size is small

Research timeShorter (mostly end with the assessment of outcome)Short term or long term (to obtain all treatments and long-term clinical outcomes as endpoints)Longer research time, long follow-up timeShorter (depends on the purpose)

OutcomeInternal validityHigh external validityInternal authenticity is not as good as RCT, and external authenticity is not as good as RWSBoth internal and external authenticity are deficient

DesignRandomization, control, prospective studyRandom or nonrandom sampling, prospective or retrospective studyProspective or retrospective or ambispective cohort studyControl, contrast

Implementation scenarioHighly standardized environmentMedical institutions, communities, homes, etc.Medical institutions and communitiesMedical institutions and communities

DataStandardization, strict specification of the collection processDiverse sources and high heterogeneityDifferent confounding factors and biasDifferent confounding factors and bias, heterogeneity