Approaches to sample size calculation for clinical trials in rare diseases

We discuss 3 alternative approaches to sample size calculation: traditional sample size calculation based on power to show a statistically significant effect, sample size calculation based on assurance, and sample size based on a decision-theoretic approach. These approaches are compared head-to-head for clinical trial situations in rare diseases. Specifically, we consider 3 case studies of rare diseases (Lyell disease, adult-onset Still disease, and cystic fibrosis) with the aim to plan the sample size for an upcoming clinical trial. We outline in detail the reasonable choice of parameters for these approaches for each of the 3 case studies and calculate sample sizes. We stress that the influence of the input parameters needs to be investigated in all approaches and recommend investigating different sample size approaches before deciding finally on the trial size. Highly influencing for the sample size are choice of treatment effect parameter in all approaches and the parameter for the additional cost of the new treatment in the decision-theoretic approach. These should therefore be discussed extensively

Adverse events during the study period (safety population^a).

<p>Adverse events during the study period (safety population<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156071#t002fn001" target="_blank">^a</a>).</p

CONSORT flow diagram of randomized patients.

<p>AE; adverse event.</p

Withheld enteral feeding for at least 24 hours (safety population^a).

<p>Withheld enteral feeding for at least 24 hours (safety population<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156071#t004fn001" target="_blank">^a</a>).</p

Adverse events associated with gastrointestinal intolerability and necrotizing enterocolitis during the 4 week treatment period (safety population^a).

<p>Adverse events associated with gastrointestinal intolerability and necrotizing enterocolitis during the 4 week treatment period (safety population<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156071#t003fn001" target="_blank">^a</a>).</p

Clinical study design and number of patients.

<p>A) The LAIF study design. The asterisk indicates a visit specific for ADA positive infants at 3 months. B) Number of randomized patients.</p

Treatment with rhBSSL improves growth in SGA infants during the 4 week treatment period.

<p>A) Growth velocity during intervention for SGA/AGA-infants. Asterisk indicates significance for SGA infants; LS mean difference (rhBSSL-placebo) of 1.95 (95% CI; 0.38, 3.52) and no significance for AGA infants; LS mean difference of -0.10 (95% CI; (-0.76, 0.57). B) Infants with a growth <15g/kg/day, odds ratio (95% CI) 0.321 (0.098, 1.045), p = 0.0592. C) Feeding utilization (LS mean rhBSSL: 120.36 g/L, LS mean placebo: 107.68 g/L). LS mean difference (95% CI): 12.68 (0.94, 24.42), p = 0.0347.</p

Treatment with rhBSSL does not improve growth in preterm infants.

<p>A) Growth velocity during intervention (rhBSSL; N = 206, placebo; N = 204). CI; confidence interval, LS mean; least square mean. B) Body weight at baseline, 4 weeks, 3 months, and 12 months adjusted age. Box plot illustrating median and Q1/Q3. Whiskers extend to lowest/highest value within 1.5 interquartile range from Q1/Q3 and outliers are indicated. C) Body length and head circumference; change from baseline at 4 weeks. D) Growth restriction during intervention.</p