The Hip Impact Protection Project: design and methods

Barton, Bruce; Birge, Stanley J.; Magaziner, Jay; Zimmerman, Sheryl; Ball, Linda; Brown, Kathleen M.; Kiel, Douglas P.

doi:10.1177/1740774508095120

Cited by 9 publications

(7 citation statements)

References 26 publications

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“…Adjustments for these factors should be made to McNemar’s test. These issues are discussed in more detail in the recent methods paper from the Hip Impact Protection Program study [45]. …”

Section: Resultsmentioning

confidence: 99%

Hip protectors: recommendations for conducting clinical trials—an international consensus statement (part II)

et al. 2009

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Introduction While hip protectors are effective in some clinical trials, many, including all in community settings, have been unable to demonstrate effectiveness. This is due partly to differences in the design and analysis. The aim of this report is to develop recommendations for subsequent clinical research. Methods In November of 2007, the International Hip Protector Research Group met to address barriers to the clinical effectiveness of hip protectors. This paper represents a consensus statement from the group on recommended methods for conducting future clinical trials of hip protectors. Results and conclusions Consensus recommendations include the following: the use of a hip protector that has undergone adequate biomechanical testing, the use of sham hip protectors, the conduct of clinical trials in populations with annual hip fracture incidence of at least 3%, a run-in period with demonstration of adequate adherence, surveillance of falls and adherence, and the inclusion of economic analyses. Larger and more costly clinical trials are required to definitively investigate effectiveness of hip protectors.

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“…Adjustments for these factors should be made to McNemar’s test. These issues are discussed in more detail in the recent methods paper from the Hip Impact Protection Program study [45]. …”

Section: Resultsmentioning

confidence: 99%

Hip protectors: recommendations for conducting clinical trials—an international consensus statement (part II)

et al. 2009

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“…The study supposedly was designed to have 90% power at p = 0.05, so that from Table , had the sample size been correct, Z should have been 3.24 ( p = 0.0012). The sample size, in terms of years of follow‐up, should not have been 1,632 person years as the design article suggests, but 1,632(3.24/1.36) 2 = 9,263 person years (about 5.7 times as many person years as proposed). Hence, the study was severely underpowered.…”

Section: Resultsmentioning

confidence: 99%

“…This was an individually matched study, where one hip was assigned to the HIP PRO device to be put in their underwear with the other hip left as a matched control without protection. The simplest way to see that there was a major error is to examine Table of the HIP PRO Design paper . It states that the expected number of falls resulting in hip fractures from the study would be 46 Control hips versus 34.5 hips assigned to HIP PRO, based on 50% compliance (explained later) and independence of the side to side outcomes (meaning very few bilateral fractures).…”

Section: Resultsmentioning

confidence: 99%

“…Calculations presume independence of outcomes for the paired experimental and control hips in the same subject. This was presumed by the HIP PRO investigators …”

Section: Methodsmentioning

confidence: 97%

“…While a peer reviewed grant may have undergone a biostatistical review or a multicenter pharmaceutical company protocol may have undergone multiple levels of review, this extra look can still provide very important information. We shall examine three real situations [1][2][3][4][5] to demonstrate the methods. One example shows a clear overestimate of the sample size needs, one a severe underestimate, and the third was spot on.…”

Section: Introductionmentioning

confidence: 99%

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Sample Size Verification for Clinical Trials

Shuster

2013

Clinical Translational Sci

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In this article, we shall provide simple methods where non-statisticians can evaluate sample size calculations for most large simple trials, as an important part of the peer review process, whether a grant, an Institutional Review Board (IRB) review, an internal scientific review committee, or a journal referee. Through the methods of the paper, not only can readers determine if there is a major disparity, but they can readily determine the correct sample size. It will be of comfort to find in most cases that the sample size computation is correct, but the implications can be major for the minority where serious errors occur. We shall provide three real examples, one where the sample size need was seriously overestimated, one (HIP PRO-test of a device to prevent hip fractures) where the sample size need was dramatically underestimated, and one where the sample size was correct. The HIP PRO case is especially troubling as it went through an NIH study section and two peer reviewed journal reports without anyone catching this sample size error of a factor of more than five-fold.

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