Communicating Treatment Effectiveness

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Utility of an Effect Size Analysis for Communicating TreatmentEffectiveness: A Case Study of Cholinesterase Inhibitors forAlzheimers DiseaseKevin R. Peters, PhD

OBJECTIVES: To highlight the utility of using an effectsize analysis to communicate the effectiveness of treatmentinterventions.DESIGN: Secondary analysis.SETTING: Previously published systematic review on cho-linesterase inhibitors (ChEIs) in Alzheimers disease.

PARTICIPANTS: Individuals with mild to moderateAlzheimers disease.INTERVENTION: Six-month randomized controlled tri-als involving a placebo group and a ChEI group (donepe-zil, galantamine, or rivastigmine).MEASUREMENTS: Cognitive function was assessedaccording to performance on the cognition subscale of theAlzheimers Disease Assessment Scale (ADAS-Cog). GlobalFunction was quantied using the Clinicians Interview-Based Impression of Change Plus (CIBIC-Plus). Harmwas dened as withdrawal from a trial because of anadverse event. Several effect size indices were computedbased on these domains: the success rate difference (SRD),

the harm rate difference (HRD), the number needed totreat (NNT) or harm (NNH), and the area under the curve(AUC). Harm:benet ratios were also computed to com-pare effect size indices across domains of function.RESULTS: In terms of benet, the NNT for cognition ran-ged from 4 to 14 (corresponding AUC values: 0.64 0.54),and the NNT for global function ranged from 6 to 100 (cor-responding AUC 0.59 0.51). In terms of harm, the NNHranged from 6 to 20 (corresponding AUC 0.58 0.53). Onlyone of the four studies had favorable harm:benet ratios inboth the cognition and global function domains.CONCLUSION: Effect size indices should be reported inclinical trials because they provide important insight into

the clinical meaningfulness of results. Additional benet isgained by comparing effect size indices across domains of

function to reveal harm:benet ratios. J Am Geriatr Soc61:11701174, 2013.

Key words: treatment; clinical meaningfulness; dementia

T raditional measures of statistical signicance(P -values) estimate the probability of obtaining resultsif the null hypothesis is true. In other words, they indicatethe probability that the results are simply due to chance.Although important, this information falls short of reveal-ing what one really wants to know about the results: themagnitude of the effect and whether it is an importanteffect.1 3 In contrast, effect size indices are better suitedfor providing this information, and unlike measures of

statistical signicance, they are largely unaffected bysample size. Effect sizes indices are available for a widerange of research contexts. 1 3

Effect size indices are often used to help gauge thepractical or clinical meaningfulness of an obtained effect(e.g., difference, relationship). With respect to treatmentinterventions, statistically signicant results are not alwaysclinically meaningful. Consider the following example; atreatment group and a placebo group is each given a list of 20 words to remember. Imagine that the treatment groupremembers an average of 15.85 words and the controlgroup remembers an average of 15.01 words. With a suf-cient number of subjects in each group this difference willbe statistically signicant, but the clinical meaningfulnessof such a small difference is questionable. It is unlikely thatthis treatment would help people remember more informa-tion in their day-to-day lives. Because effect size indiceshelp in assessing the clinical meaningfulness of a givenresult, they complement traditional measures of statisticalsignicance and should be reported whenever possible.

Although the reporting of effect sizes is encouraged inmany disciplines, there are some that do not regularly followthis practice. For example, in a systematic review of 57

From the Department of Psychology, Trent University, Peterborough,Ontario, Canada.

Address correspondence to Kevin R. Peters, Department of Psychology,Trent University, 1600 West Bank Drive, Peterborough, Ontario K9J 7B8,Canada. E-mail: [email protected]

DOI: 10.1111/jgs.12308

JAGS 61:11701174, 2013

2013, Copyright the Authors Journal compilation 2013, The American Geriatrics Society 0002-8614/13/$15.00


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randomized control trials of pharmacological interventionsfor dementia, the clinical meaningfulness of results was dis-cussed in fewer than half of these trials (46%). 4 When clini-cal meaningfulness was mentioned, the majority of authorsused opinion-based assessments. Measures of effect sizewere not reported in any of the 57 studies.

At the aggregate level, the most commonly reportedeffect size indices in meta-analyses are the standardized

mean difference (e.g., Cohens) for continuous measuresand the odds ratio for binary measures. It has been arguedthat other effect size indices provide better estimates of clinical meaningfulness, 3 including number needed to treat(NNT), area under the curve (AUC), and success rate dif-ference (SRD). In the area of dementia research at least,few individual trials or meta-analyses compute these indi-ces, although some have. 5,6 In addition, effect size indicesare typically reported in a unidimensional sense; they areconsidered individually for each scale or outcome, andauthors rarely compare and contrast these indices acrossdifferent outcome domains.

The purpose of this study is to highlight the utilityof an effect size analysis for communicating the effective-ness of treatment interventions. To achieve this goal, thisstudy examines a subset of randomized clinical trials thatwere included in a published Cochrane systematic reviewon the effectiveness of cholinesterase inhibitors (ChEIs)for Alzheimers disease (AD).7 In addition to computingeffect size indices for individual domains of function(cognition, global function, and harm), harm:benetratios were also systematically generated and comparedacross these domains of function. The goal of thissecondary analysis is not to comment directly on theeffectiveness of the ChEIs for AD but rather to showcasehow such an approach can be benecial for communicat-ing the clinical meaningfulness of treatment interventionsin the future. The intended audience is not only authorsof clinical trial reports, but also journal editors, health-care policy-makers, and the more general audience of readers.

METHODS

This study is a secondary analysis of a previously pub-lished Cochrane systematic review on ChEIs for AD. 7

Although that review included 10 trials, only four of theseprovided sufcient data to allow all of the effect sizeindices of interest to be computed. For consistency, thenames of the trials used in that review have been kept:

DON-302,8

GAL-INT-Wilcock,9

GAL-USA-Raskind,10

and RIV-B303. 11

Individual Domains of Function

Cognition was assessed using the cognition subscale of the Alzheimers Disease Assessment Scale (ADAS-Cog).This scale ranges from 0 to 70, with higher scores indi-cating greater impairment. 12 For each study, the numberof responders on the ADAS-Cog (those who improved by

4 points) in each group was obtained from the individ-ual studies, because this is a commonly used criterion inthe eld. The success rate difference (SRD; also known as

the absolute difference) was then computed along with

95% condence intervals (CIs) for each trial. Two effectsize indices were then calculated using these SRD values.First, the number needed to treat (NNT 13 ), which esti-mates the number of individuals that need to be treatedwith a given intervention (e.g., ChEI) to obtain one moresuccessful outcome than would have been obtained if they had been treated with a different intervention (e.g.,placebo), was computed. The formula for the NNT is

1/(success rate difference); this formula was used to com-pute the point estimates and the 95% CIs. Lower NNTvalues are favorable. The 95% CIs of the SRD were cal-culated using the prop.test function in the R softwarepackage. 14

Second, the AUC, 3 which estimates the probability of a participant in the drug group having a better outcomethan a participant in the placebo group if one were to ran-domly sample participants from each group, was com-puted. This index is referred to as AUC-positive, and it iscomputed as 0.5 (success rate difference + 1). This formulawas used to compute the point estimates and 95% CIsbased on the SRD values described above. An AUC valueof 0.50 indicates no group difference; higher AUC valuesare favorable.

Global Function was assessed using the ClinicianInterview-Based Impression of Change Plus (CIBIC-Plus),which is based on the Alzheimers Disease CooperativeStudy Clinical Global Impression of Change scale. 15

Without access to laboratory or psychometric testingresults, the clinician forms an impression of change that isbased on separate interviews with the individual and thecaregiver. The interview covers the domains of general,cognitive, behavior, and activities of daily living and usesa 7-point Likert scale (1, marked improvement; 4, nochange; 7, marked worsening). Responders were individu-als who showed improvement on the CIBIC-Plus (scores of 1 3) over the trial. As with the cognition domain, pointestimates and 95% CIs were computed for the SRD, thenthese values were used to compute the NNT and AUC-positive for each trial.

Harm was assessed by comparing the number of par-ticipants who dropped out of each RCT because of anadverse event from each group. It was felt that this was amore-conservative measure of harm than if the total num-ber of dropouts in each group had simply been used,because there are various reasons why participants dropout of a study. The same effect size indices computed forthe cognition and global function domains were alsocomputed here, but they were called the harm rate

difference (HRD), number needed to harm (NNH), andAUC-negative to reect their negative nature.

Multidimensional Analysis

To illustrate the utility of comparing effect size indicesacross domains of function, two harm:benet ratio scoreswere computed: the harm:cognition score and the harm:glo-bal function score. For each of these ratio scores, the NNHvalue was divided by the respective NNT for each trial.Ratios of 1.0 indicate no difference (harm = benet), ratiosgreater than 1.0 indicate more benet than harm, and ratiosless than 1.0 indicate more harm than benet. This

approach was based on a method previously developed16

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for interpreting the clinical meaningfulness of results of weight loss intervention trials.

RESULTS

Individual Domains of Function

The effect size indices for the four RCTs are reported in

Table 1. For the cognition domain, SRD values rangedfrom 0.07 to 0.27, NNT values ranged from 14 to 4, andAUC-positive values ranged from 0.54 to 0.64. The 95%CI for the SRD in the RIV-B303 trial crossed 0 ( 0.01 to0.15), indicating a statistically nonsignicant benet of thedrug for cognition. The corresponding NNT for this effectis 14, and the 95% CI ( 100 to 7) does not contain thispoint estimate. This is a known limitation of the NNT foreffects that are not statistically signicant, which compli-cates its interpretation. 17,18 In addition, the AUC-positivevalue for the RIV-B303 trial was 0.54, and the 95% CIincluded 0.50, which is the value of this statistic whenthere is no difference between the two groups. Accord-ingly, in this case, a SRD of 0.07, a NNT of 14, and anAUC-positive value of 0.54 are all associated with statisti-cally nonsignicant differences between the two groups.

The SRD values in the global function domain rangedfrom 0.01 to 0.17 and were generally lower than thosereported for the cognition domain (the drugs benettedcognition more than global function). The CIs for the twogalantamine trials crossed 0, indicating no statistically

signicant benet of the drug over placebo. The NNTvalues ranged from 100 to 6, and the AUC-positive valuesranged from 0.51 to 0.59.

For the harm domain, the HRD values ranged from0.05 to 0.16. The HRD CI crossed 0 in the GAL-INT-Wilcock trial, indicating that the two groups did not differsignicantly with respect to the number of withdrawalsdue to an adverse event, but the number of such with-

drawals was signicantly greater in the drug group than inthe placebo group for the other three trials. The NNHranged from 20 to 6, and the AUC-negative values rangedfrom 0.53 to 0.58.

Multidimensional Analysis

Figure 1 shows the harm:cognition and the harm:globalfunction ratio scores for each of the four trials. The bestpair of outcomes is observed for the DON-302 trial, bothof the ratios are greater than 1.0. The ratio of 2.5 forharm:cognition indicates that the NNH (10) is 2.5 timesas great as the NNT (4), and in this trial, the drug benet-ted cognition more than global function. The results forthe GAL-INT-Wilcock trial are inconsistent: Althoughthere is a positive outcome for cognition (the NNH is 2.86times as great as the NNT), there is more harm than bene-t for global function (the NNT is 5 times as great as theNNH). The other two studies, GAL-USA-Raskind andRIV-B303, show no net benet at all or some degree of harm.

Table 1. Responder Data and Effect Size Indices

Domain or Index

Study

DON-302 GAL-INT-Wilcock GAL-USA-Raskind RIV-B303

CognitionDrug responders, n/N 80/150 64/220 67/202 57/242Placebo responders, n/N 41/153 32/215 34/207 39/238SRD (95% CI) 0.27 (0.15 to 0.38) 0.14 (0.06 to 0.22) 0.17 (0.08 to 0.26) 0.07 ( 0.01 to 0.15)a

NNT (95% CI) 4 (7 to 3) 7 (17 to 5) 6 (13 to 4) 14 (100 to 7)b

AUC-positive (95% CI) 0.64 (0.58 to 0.69) 0.57 (0.53 to 0.61) 0.59 (0.54 to 0.63) 0.54 (0.50 to 0.58)Global Function

Drug responders, n/N 37/149 36/206 37/186 80/219Placebo responders, n/N 17/152 33/203 27/196 46/230SRD (95% CI) 0.14 (0.04 to 0.23) 0.01 ( 0.07 to 0.09)a 0.06 ( 0.02 to 0.14)a 0.17 (0.08 to 0.25)NNT (95% CI) 7 (25 to 4) 100 (14 to 11)b 17 ( 50 to 7)b 6 (13 to 4)AUC-positive (95% CI) 0.57 (0.52 to 0.62) 0.51 (0.47 to 0.55) 0.53 (0.49 to 0.57) 0.59 (0.54 to 0.63)

HarmDrug withdrawals due toadverse events, n/N

26/157 31/220 49/212 55/242

Placebo withdrawals dueto adverse events, n/N

11/162 19/215 16/213 16/239

Harm rate difference (95% CI) 0.10 (0.02 to 0.17) 0.05 ( 0.01 to 0.12)a 0.16 (0.08 to 0.23) 0.16 (0.10 to 0.23)NNH (95% CI) 10 (50 to 6) 20 (100 to 8)b 6 (13 to 4) 6 (10 to 4)AUC-negative (95% CI) 0.55 (0.51 to 0.59) 0.53 (0.50 to 0.56) 0.58 (0.54 to 0.62) 0.58 (0.55 to 0.62)

SRD, success rate difference; AUC, area under the curve.a 95% condence intervals (CIs) that cross 0 indicate that the group difference is not statistically signicant.b Negative number needed to treat (NNT) indicate that participants in the placebo group are doing better than those in the drug group, and numberneeded to harm (NNH) indicate that participants in the placebo group are doing worse. For example, a NNT of 100 indicates that 100 participantswould need to be treated with placebo to obtain one additional successful outcome than would have been obtained they had been treated with thedrug. The CI here does not actually contain the point estimate because the effect is not statistically signicant; this is a well-known limitation of NNTand NNH.

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DISCUSSION

This investigation highlights two important points. First,effect size indices help to interpret the clinical meaningful-ness of RCT results. For example, consider the AUC-posi-tive values reported here; the highest was 0.64. Although inthis trial, the number of responders on the ADAS-Cog inthe drug group was signicantly greater than in the placebogroup (SRD = 0.27, 95% CI = 0.15 0.38), this AUC is notlarge considering that a value of 0.50 indicates an equalprobability of success if one were to sample a participantfrom each group. The information from the effect size indi-ces provide a meaningful context for interpreting trialresults and therefore complement the traditional approachof relying on measures of statistical signicance alone.

Second, there is value in comparing effect size indicesacross outcome domains. Harm:benet ratios were com-puted for the cognition and global function domains. Thisanalysis revealed that only one of the four RCTs showedconsistent evidence of more benet than harm in these twodomains. In addition, the GAL-USA-Raskind and the RIV-B303 studies nicely illustrate the limitations of looking atone index in isolation. The NNT values in these two studiesranged from 6 to 17, which would be considered very good

considering that the azidothymidine drug trial for AIDSwas halted early with a NNT of 9 19 and the PhysiciansHealth Study examining the benet of aspirin was alsohalted early with a NNT of 130. 20 However, in the GAL-USA-Raskind and the RIV-B303 studies, the interpretationof these NNT values changes considerably when one takesinto account the fact that the NNH in these two trials is 6,and the harm:benet ratios illustrate this point. Thisapproach of directly comparing the harm and benet of atreatment intervention is more consistent with what physi-cians do when treating patients; they compare the potentialharm and potential benet of a medication to inform theirtherapeutic decision-making. Rarely do physicians ponder

the probability of whether the results of a given trial were

simply due to sampling error (the information provided bya P -value), and rarely do they consider the harms and bene-ts of a medication in isolation from one another.

Placing the current approach into a larger context, theCONSORT guidelines 21 for the reporting of statistics inparallel-group randomized trials recommends reporting theabsolute and relative effect sizes for binary outcomes (Item17b), and they state that reporting the NNT and NNHcan be helpful (Items 17a and 21). These guidelines servewell their intended goal as being minimal requirements forreporting of clinical trials, but the NNT, the NNH, theAUC estimates, and the harm:benet ratios presented hereshould be reported. These effect sizes and ratios are usefulin conveying the clinical meaningfulness of trial results andwill appeal to a much wider audience.

There are several notable limitations with this second-ary analysis. First, effect size indices were computed basedon binary outcomes only (e.g., improved or not, withdrewfrom RCT due to an adverse event or not). Although theeffect size indices reported here have been shown to dem-onstrate clinical meaningfulness, 3 future research shouldconsider expanding such an approach to include effect sizeindices based on continuous outcome measures.

A second limitation is that in computing harm:benet

ratios, the severity of the measures of harm and benetwere implicitly equated, but it is difcult to say whetherone can consider the act of withdrawing from an RCT dueto an adverse event as being of the same magnitude asshowing an improvement of 4 or more points on theADAS-Cog. Part of the problem is that this eld lackswhat has been referred to as a language of benet forAD treatments. 22 Is it fair to state that a 4-point improve-ment on the ADAS-Cog is a clinically meaningful benet?To make this approach more successful, agreement onwhat constitutes benet and what constitutes harm isneeded. Such clarication would make it easier for clini-cians to take into account their patients preferences in a

shared, or informed, decision-making model.23,24

For

Figure 1. Cognition and global function harm:benet ratios for each study. Ratios equal to 1.00 indicate no difference betweenthe amount of harm and benet. Values greater than 1.00 indicate more benet than harm; values less than 1.00 indicate moreharm than benet. The x-axis is a logarithmic scale to reect equal spacing of values above and below 1.00. NNH, number

needed to harm; NNT, number needed to treat.

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example, some people may place more importance on anydegree of improvement regardless of the adverse eventstypically associated with ChEIs; in contrast, other peoplemay feel that the degree of benet typically achieved bytaking these drugs does not outweigh the risks for adverseevents. The approach illustrated here is useful for commu-nicating benets and harms to individuals, policy-makers,and the lay public, but there should also be more discus-

sion of how to dene these terms better.Although the task of developing more clinically mean-ingful measures of benet and harm will be challenging, itwould allow a much more-nuanced effect size analysisapproach to be adopted. For example, an approach hasbeen outlined in which individuals baseline risks (the risksassociated with not being treated as well as risks due toadverse events) and preferences regarding their assessmentof the benets and harms factor in the calculation of aNNT:NNH ratio. 25 This metric is called the likelihood of being helped or harmed. It is not feasible to apply thisanalysis here, because it would be difcult to ask people tocomment on how important a 4-point improvement on theADS-Cog would be to them as opposed to how importantit would be to avoid adverse events associated with ChEIs.Thus, the simpler approach adopted here is a useful rststep in developing more-useful methods for communicatingthe benet and harm of treatments.

Finally, more work is needed to determine how largethese harm:benet ratios need to be to signify clinicalmeaningfulness. In other words, how much larger does theNNH need to be than the NNT: 2, 3, or 4 times greater?Again, these decisions will be dependent upon denitionsof benet and harm and the preferences of individuals. Forexample, the NNH will need to be considerably higherthan the NNT if the denition of harm is a serious event(e.g., stroke) than if it is a less-serious event (e.g., nausea).The cost and ease of use of treatments will also factor intothese equations. As indicated previously, 3 although theNNT to prevent one additional heart attack in the aspiringroup of the Physicians Health Study was 130, this treat-ment is cheap and easy to administer.

In the future, researchers conducting clinical trialsought to have a clear understanding a priori of what willconstitute clinically meaningful benet and harm ratherthan relying simply on the statistical signicance of theresults obtained. The goals of this secondary analysis wereto offer a useful approach to communicating the effective-ness of treatment interventions and to initiate a largerdiscourse around these issues. Consensus among clinicians

and researchers on these issues will be crucial to identifyingsafe and effective treatment interventions for dementia.

ACKNOWLEDGMENTS

A poster based on this work was presented at the 2012 Alz-heimer Association International Conference held in Van-couver, British Columbia, Canada. The author gratefullyacknowledges the assistance of Ms. Jaclyn Orsetto for herhelp in preparing the manuscript, and Dr. Peter White-house for helpful comments on an earlier draft of this man-uscript.

Conict of Interest: This study was supported by an

operating grant from the Canadian Institutes of Health

Research. The author has no nancial conicts to dis-close.

Author Contributions: KRP designed the study, con-ducted all analyses, and wrote the manuscript.

Sponsors Role: None.

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C o p y r i g h t o f J o u r n a l o f t h e A m e r i c a n G e r i a t r i c s S o c i e t y i a n d i t s c o n t e n t m a y n o t b e c o p i e d o r e m a i l e d t o m u l t i p l e s i t h e c o p y r i g h t h o l d e r ' s e x p r e s s w r i t t e n p e r m i s s i o n . H o w e ve m a i l a r t i c l e s f o r i n d i v i d u a l u s e .

Communicating Treatment Effectiveness

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