Table. 6.

Table. 6.

Bias treatment codes related to hematopoietic stem cell transplantation

Category Description of the bias

 Subcategory
Confounding The measure of association between treatment and outcome is distorted by the effect of variables, which are risk factors for the targeted outcome.
Confounding by indication The clinical condition that determined the prescription of the treatment is associated with the effect, acting as a confounding factor.
Time-dependent confounding A time-dependent variable acts as a confounding factor between the current exposure and outcome, and as an intermediary between prior and current exposure.
Unmeasured/residual confounding There is not enough information about all the relevant confounding factors known, unknown or difficult to measure. If confounding cannot be controlled, the residual confounding effect of some factors remains in the effect that is observed.
Healthy user/adherer effect Access to health care resources is associated with a higher education and health-seeking behavior. Patients who comply with prolonged treatment periods tend to be healthier.
Selection bias The sample population is not representative of the population to which the results will be extrapolated.
Protopathic bias The treatment is associated with subclinical disease stages (an early manifestation of the still undiagnosed condition under study gives rise to prescription of the treatment).
Losses to follow-up (informative censoring) The mechanism that triggers discontinuity of treatment is associated with the risk of observing the outcome of interest.
Depletion of susceptibles (prevalent user bias) The inclusion of prevalent instead of incident users entails insufficient verification of the adverse effects that occur at the beginning of treatment (those susceptible to the effect have interrupted the treatment).
Missing data In multivariate analyses, observations that lack some values of a variable included in the model tend to be eliminated.
Measurement bias Data on true exposures, outcomes, and other variables are recorded in the form of indicators that do not accurately reflect reality.
Misclassification bias The association between treatment and outcome is distorted by errors, owing to the way variables of interest are measured in comparison groups.
Misclassification of exposure The measure of exposure of a given treatment is not an exact reflection of its real use.
Misclassification of outcome There is an error in the diagnosis.
Time-related bias Follow-up time and exposure status are inadequately considered in the study-design or analysis stages.
Immortal time bias A period during which the study event cannot occur is included in the follow-up or is excluded from analysis due to an incorrect definition at the start of follow-up.
Immeasurable time bias A period during which follow-up is ignored and thus misclassified as an unexposed period, since outpatient prescriptions that define exposure cannot occur.
Time-window bias Using time-windows of different lengths between cases and controls to define time-dependent exposures prevents subjects from having the same opportunity time to receive prescriptions.
Time-lag bias Treatment comparisons are conducted at different stages of the disease, which introduces bias related to disease duration and progression.
Clin Pediatr Hematol Oncol 2022;29:1-11
© 2022 Clin Pediatr Hematol Oncol