Patient Expectancy and Post-chemotherapy Nausea: A Meta-analysis

ann. behav. med. (2010) 40:3 14 DOI 10.1007/s12160-010-9186-4 ORIGINAL ARTICLE Patient Expectancy and Post-chemotherapy Nausea: A Meta-analysis Ben Colagiuri, B.Psych, Ph.D. & Robert Zachariae, M.D.Sci. Published online: 13 April 2010 # The Society of Behavioral Medicine 2010 Abstract Background Post-chemotherapy nausea remains a significant burden to cancer patients. While some studies indicate that expecting nausea is predictive of experiencing nausea, there are a number of conflicting findings. Purpose The purpose of this study was to conduct a metaanalytic review to determine the strength of the relationship between expectancy and post-chemotherapy nausea. Methods The findings from 17 relevant studies (n=2,400) identified through systematic searches of Medline, PsycInfo, and Cinhal were analyzed using a combination of meta-analytic techniques. Results Overall, there was a robust positive association between expectancy and post-chemotherapy nausea (ESr= 0.18, equivalent to Cohen s d=0.35), suggesting that patients with stronger expectancies experience more chemotherapy-induced nausea. Although weaker associations were found in studies employing multivariate analysis, specifically controlling for a history of nausea, and involving breast cancer patients, none of the moderators assessed were statistically significant. Conclusions These findings suggest that patient expectancies may contribute to post-chemotherapy nausea and that expectancy-based manipulations may provide a useful intervention strategy. Keywords Expectancy. Nausea. Chemotherapy. Placebo effect B. Colagiuri (*) School of Psychology, A18, University of Sydney, Sydney, NSW 2006, Australia e-mail: benc@psych.usyd.edu.au R. Zachariae Psychooncology Research Unit, Aarhus University Hospital, Aarhus, Denmark Introduction Despite significant improvement in methods of preventing and controlling emesis, up to 75% of patients undergoing chemotherapy continue to report nausea at some point during their treatment [1 3]. Nausea is inherently unpleasant, is often rated as one of the most debilitating chemotherapy-induced side effects [4 6], and significantly detracts from patients quality of life (QoL) [7 12]. It can also have a detrimental impact on chemotherapy outcomes if reductions in drug dosage are required to manage it or if it decreases patients motivation to follow their treatment regimen [6]. Thus, reducing post-chemotherapy nausea is likely to improve patients QoL and may facilitate more effective anticancer treatment. While the emetic potential of the chemotherapy regimen affects the likelihood of post-chemotherapy nausea [13], this factor alone cannot fully explain the variation in patients reports of post-chemotherapy nausea. Instead, factors such as younger age [14 16], female gender [14, 17], lower QoL [10], experiencing nausea/emesis during pregnancy [14], susceptibility to motion sickness [2, 18, 19], and stronger expectancies for nausea [10, 20, 21] also appear related to post-chemotherapy nausea. Of these predictors, patient expectancy is unique in that it is open to manipulation and may serve as a possible point of intervention for reducing post-chemotherapy nausea and its burden on patients QoL. Establishing if expectancies contribute to post-chemotherapy nausea is, therefore, important for determining the potential utility of expectancy-based interventions. Although some studies have found a significant positive relationship between patients pretreatment expectancies and post-chemotherapy nausea [10, 20, 21], other studies have failed to find such an association [22, 23]. Further, in other studies, expectancy has been found to predict

4 ann. behav. med. (2010) 40:3 14 particular nausea outcomes but not others. For example, Jacobsen et al. [19] found that expectancy predicted the occurrence, severity, and duration of nausea but not the frequency, and Roscoe et al. [24] found that expectancy predicted the occurrence of severe nausea but not its average severity. Thus, there appears to be both betweenand within-study variation in estimates of the association between expectancy and various dimensions of postchemotherapy nausea. While these studies share their basic design, with expectancies for nausea being assessed before a chemotherapy infusion and subsequent post-chemotherapy nausea being recorded, there are a number of potentially important differences in methodology, statistical analyses, and sample characteristics that could explain these variations. One such factor is the nausea outcome being assessed. One as yet untested possibility is that expecting nausea may increase its severity, but not its occurrence. That is, expectancy may worsen post-chemotherapy nausea in those already experiencing it, but may not actually produce nausea in and of itself. A second potentially important methodological factor is the timing of the expectancy assessment. For instance, measuring expectancies after patients have had some experience with chemotherapy [20, 25] might lead to a stronger relationship between expectancy and nausea because these patients may be more aware of their susceptibility to chemotherapy-induced nausea than patients who have not yet received any chemotherapy. If so, then patient expectancy may simply serve as a marker for susceptibility to nausea, rather than actually contributing to its occurrence, frequency, or severity. An important analytical factor might be whether or not the analysis controls for patients history of nausea in other settings, such as, susceptibility to motion sickness and nausea during pregnancy. As with measuring expectancy after the patients have received some chemotherapy, studies that fail to control for a history of nausea in other settings [23, 26, 27] might overestimate the contribution of expectancy to post-chemotherapy nausea if the patients expectancies reflect an accurate acknowledgement of their general susceptibility to nausea. The current study used meta-analysis to examine the relationship between patients expectancies of postchemotherapy nausea and their subsequent reports of nausea in all relevant published studies to date and to determine whether any methodological, analytical, or sample-related factors moderated the strength of this association. To achieve the latter, we compared estimates of effect sizes for studies assessing different nausea outcomes, namely, severity, occurrence, and frequency. We also compared effect sizes across studies based on various methodological and analytical factors, including level of statistical control, specific control for history of nausea, timing of the expectancy and nausea assessments, emetic potential of the chemotherapy regimen, cancer type, and gender. Methods Search Strategy Articles were identified through computerized literature searches. Medline (from 1950), PsycInfo (from 1806), and Cinhal (from 1982) were searched for English publications up to June 2009 using the search terms expectancy, expectancies, expectation$, expected, placebo effect$, OR placebo response$ in combination with chemotherapy AND nausea OR emesis. The reference lists of publications identified through the electronic search were also screened for additional relevant articles. Selection Criteria To be included, studies needed to measure patient expectancies for post-chemotherapy nausea and report on the subsequent occurrence, severity, or frequency of postchemotherapy nausea. Assessment of expectancies could include asking patients how likely or how severe they expected nausea to be following their chemotherapy treatment. In terms of nausea, occurrence was considered a dichotomous classification of whether or not nausea was reported following chemotherapy. Nausea severity referred to the average severity of post-chemotherapy nausea, measured either on Likert-type scales or visual analogue scales. Nausea frequency referred to either the number of times a patient experienced nausea following a chemotherapy infusion or the number of days nausea was reported following a single chemotherapy infusion. Articles focusing solely on anticipatory nausea were not included in the current review. Moderators In addition to assessing the general association between expectancy and post-chemotherapy nausea, we explored whether the association was moderated by 1) the nausea outcome measure, 2) any statistical control, 3) specific statistical control for a history of nausea in other settings, 4) timing of the expectancy and nausea assessments, 5) emetic potential of the chemotherapy regimen, 6) cancer type, and 7) gender. The nausea outcomes compared were those described above, namely, severity, occurrence, and frequency. Any statistical control referred to whether the association between expectancy and nausea was assessed via univariate or multivariate analysis, with multivariate analysis including

ann. behav. med. (2010) 40:3 14 5 control for any other potentially confounding factor. Specific control for history of nausea referred to whether or not the analysis controlled for a history of nausea in other settings. Studies considered to have controlled for a history of nausea included at least one of the following as covariates in their analysis: susceptibility to motion sickness, nausea during pregnancy, or nausea in response to food. For timing of expectancy and nausea assessments, studies were categorized into three groups. The first included studies that measured expectancy prior to the first chemotherapy infusion and nausea following this infusion. The second included studies that measured expectancy prior to the first chemotherapy infusion, but assessed nausea after multiple infusions or any infusion other than the first. The third included studies that measured expectancy before multiple infusions or before any infusion other than the first and assessed nausea after multiple infusions or any infusion other than the first. The emetic potential of the chemotherapy used in each study was estimated based on the classification suggested by Hesketh [13]. To do this, the chemotherapy regimens described in each study were analyzed, and the study was given an emetic potential score from 1.0 to 4.0 based on the agent with the highest emetic potential in the treatment regimen. If different subgroups of patients had received different types of chemotherapy, a weighted average emetic potential score was calculated based on the number of patients in each subgroup. In addition to this, emetic potential scores were dichotomized into 1) high ( 3) and 2) low (<3), and the relationship between expectancy and post-chemotherapy nausea was compared across these studies. Because the studies assessed a number of breast cancer samples, as well as some heterogeneous cancer samples, comparisons of expectancy and post-chemotherapy nausea were made between breast cancer and the mixed samples. To assess the role of gender, we used the percentage of female patients as a continuous moderator in a metaregression. Study Coding The authors reviewed the retrieved articles and independently coded the sample characteristics, the independent and the dependent variables, and whether the study fulfilled the inclusion criteria. Differences were discussed, and a final assessment was negotiated for each study. There was no documented protocol for data collection. Computing Effect Sizes As suggested by Rosenthal and Rubin [28], we used the effect size correlation coefficient (ESr) as the global effect size, with positive values indicating that expectancy is associated with subsequent greater occurrence, severity, or frequency of post-chemotherapy nausea, i.e., an association in the hypothesized direction. The average effect size was calculated as a weighted mean using the inverse variance method giving studies with larger sample size greater weight than studies with small sample size. If more than one effect size had been computed for each study, they were combined when calculating the global effect size for the outcome variable at interest. In some articles, mainly those presenting results of univariate analyses, effect sizes (Pearson s r) were directly available [21, 22, 24, 27]. Others presented results as mean and standard deviations of post-chemotherapy nausea in high and low expectancy groups [19, 29] or as Chi-square statistics [20, 23, 26]. In these cases, ESr was estimated from formulas suggested in the literature. In other studies using multivariate statistics, the association was presented as a change in R square [2, 30], Odds Ratios [24, 25, 31] or Beta-coefficients [10, 19, 22, 32, 33]. While change in R square was directly transformed, ESrs were estimated from Odds ratios using the formulas suggested by Rosenthal [34, 35], and from Beta s using the estimation procedure suggested by Peterson and Brown [36]. In two articles [24, 33], data for some results were only presented as nonsignificant. In these cases, the authors were contacted to determine the appropriate statistics for the non-reported results. However, in one case [33] no response was received, so the effect size for these results was set to 0.0. When several results were available for the same association, e.g., for several infusions [20, 31], acute and delayed nausea [25, 29, 33], or for two closely associated independent measures, e.g., expected nausea and expected worst nausea [24], the effect sizes were combined into an average effect size. For an outcome or moderator to be included in a separate meta-analysis, at least three independent effect sizes had to be available. Independence of Results If an article reported results for more than one outcome, an average effect size across nausea assessment type was calculated, so that only one result per study was used in each model. Heterogeneity To quantify levels of heterogeneity, we calculated Q, a Chisquare statistic [37]. Due to the risk of low statistical power as a consequence of small sample sizes, we followed statistical recommendations and used a p value of 0.10 to determine statistical significance when assessing heterogeneity. In case of statistical significance, the effect size measures from each individual study were aggregated using a random-effects model [38].

6 ann. behav. med. (2010) 40:3 14 Quality Assessment As the utility of assigning a quality score to each study and using this score to weight the results in meta-analyses is controversial [39], we chose not to follow a formal scoring procedure, and have attempted to address relevant methodological and analytical factors by investigating whether they moderate the relationship between expectancy and post-chemotherapy nausea. Publication Bias Publication bias, a widespread problem when conducting meta-analyses [40], was evaluated with the commonly used graphical funnel plot method [41], the Egger test, a widely used test for funnel plot assymetry [41], and calculation of failsafe numbers [42, 43]. The failsafe number addresses the file-drawer problem, i.e., the possibility that unpublished studies might exist that contradict the results of the meta-analysis, and refers to the minimum number of unpublished studies reporting null findings that would be required to reach another conclusion in a specific metaanalysis. A failsafe number exceeding 5K+10, with K being the number of studies included in the meta-analysis, is considered evidence for a robust result [34, 35]. If the results of the funnel plot or the Egger test were suggestive of potential publication bias, an adjusted effect size was estimated using Duval and Tweedie s [44] trim-and-fill method, which imputes missing results and recalculates the effect size accordingly. Analytical Strategy First, we tested whether there was a significant general positive relationship between expectancy and post-chemotherapy nausea by calculating the overall effect size for all studies included, using a fixed or random model approach depending on whether there were signs of heterogeneity (p<0.10). Next, we explored the role of potential moderators of relationship using meta- ANOVAs for categorical moderators and meta-regression for continuous moderators. The meta-analysis was conducted using Comprehensive Meta-Analysis, version 2.2 [45]. The PRISMA guidelines for reporting meta-analyses [46, 47] were followed. Results Study Selection The literature search in the electronic databases identified a total of 17 independent studies published in 16 articles reporting results concerning associations between some measure of expected nausea assessed before one or more chemotherapy infusions and some measure of postchemotherapy nausea measured after one or more chemotherapy infusions. The search of Medline, PsycInfo, and Cinhal databases provided a total of 244 citations. After removing duplicates and non-peer-reviewed journal articles, 205 references remained. Of these, 189 articles were discarded because after reviewing the abstracts it appeared that these papers clearly did not meet the criteria. The full text of the remaining 16 citations was examined in more detail, all of which met the inclusion criteria. The reference lists of these articles were screened for additional studies that the electronic search could have missed. However, no further studies were identified. We were also aware of an article in press [16] thatassessedthe association between expectancy and post-chemotherapy nausea. The relevant analysis conducted in that article, however, is based on composite data from studies already identified in our literature search [10, 24] and therefore, would not have met the criteria for inclusion in the current meta-analysis. Study Characteristics The 17 studies included in the meta-analysis investigated a total of 2,400 participants, with an average sample size of 141 (range 29 (2) to 671 (10)), after adjusting the sample sizes according to the number of participants that the effect size calculations were based upon. The study characteristics are summarized in Table 1. The type of cancer most often studied was breast cancer, and the percentage of women in the studies was generally high, ranging from 54% [22] to 100% [2, 19 21, 24, 25, 29, 31, 33]. As seen in Table 1, 14 studies measured nausea expectancy prior to the first infusion, while the remaining three studies measured expectancy after multiple infusions or any infusion other than the first. Several assessment methods had been used, including whether the patients expected to experience nausea or the expected severity of nausea on Likert-type scales. Post-chemotherapy nausea had been assessed after the first infusion in eight studies and after one or more of the subsequent infusions in 11 studies. Again, the assessment methods varied, with most studies measuring nausea severity (12 studies), followed by nausea occurrence (six studies), frequency (four studies), duration (two studies), and peak nausea (three studies). The emetic potential scores of the chemotherapy regimens used ranged from 2.4 to 4.0, with the chemotherapy used classified as having high ( 3) emetic potential in ten studies and low (<3) in four studies. It was not possible to estimate the emetic potential for the three remaining studies. Nine studies presented results from univariate analyses without controlling for potential confounders and yielded a total of 11 effect sizes. Multivariate statistics, controlling for one or more potential confounders,

ann. behav. med. (2010) 40:3 14 7 Table 1 Study characteristics and effect sizes Study N a Moderators Effect sizes (ESr) Cancer type Percent women (%) Control for nausea history Expectancy before infusion no. Nausea after infusion no. Emetic potential b (high, low) c Post-therapy nausea assessment Univariate (no control) Multivariate (statistical control) d 1. Cassileth et al. [23] 35 Mixed 79 No First Other Occurrence 0.07 2. Jacobsen et al. [19] 45 Breast 100 No First Other 4.0 (high) Duration 0.25 Frequency 0.23 Severity 0.24 3. Haut et al. [32] 36 Mixed 56 Yes First Other 2.6 (low) Frequency 0.57 Severity 0.49 4. Andrykowski & Gregg [22] 65 Mixed 54 No Other Other 2.4 (low) Frequency 0.16 0.21 Severity 0.15 0.09 5. Rhodes et al. [26] 329 Mixed 67 No First First Occurrence 0.17 6. Watson et al. [31] 84 Breast 100 Yes First Other 2.8 (low) Occurrence e 0.07 7. Montgomery & Bovbjerg [20] 52 Breast 100 No First First 4.0 (high) Occurrence 0.15 Other Other Occurrence 0.30 Other Other Occurrence 0.51 8. Roscoe et al. [2] (study 1) f 29 Gynecol. 100 Yes First Other 3.3 (high) Severity 0.42 9. Roscoe et al. [3] (study 2) f 81 Mixed 88 Yes First Other 2.9 (low) Severity 0.22 10. Molassiotis et al. [33] 71 Breast 100 Yes First First 4.0 (high) Duration g 0.15 Frequency g 0.00 h Severity 0.00 h 11. Roscoe et al. [24] 194 Breast 100 Yes First First 3.5 (high) Occurrence i 0.04 Severity i 0.18

Table 1 (continued) Study N a Moderators Effect sizes (ESr) Cancer type Percent women (%) Control for nausea history Expectancy before infusion no. Nausea after infusion no. Emetic potential b (high, low) c Post-therapy nausea assessment Univariate (no control) Multivariate (statistical control) d 12. Olver et al. [30] 89 Mixed 63 No First First Severity 0.22 13. Booth et al. [25] 143 Breast 100 Yes Other Other 3.8 (high) Occurrence 0.27 g 14. Higgins et al. [29] 56 Breast 100 No First First 3.8 (high) Severity 0.15 g 15. Zachariae et al. [21] 98 Breast 100 No First Other 3.5 (high) Severity 0.24 0.15 16. Colagiuri et al. [10] 671 Mixed j 94 Yes First First 3.0 (high) Peak nausea 0.14 Severity 0.14 17. Shelke et al. [27] 322 Mixed 73 No First First 3.1 (high) Peak nausea 0.30 k Severity 0.24 k Summary K: 17 Breast: 8 Total: 86 Yes: 8 First: 9 First: 9 high: 10 Severity: 12 Number of N: Mixed: 8 Mixed: 80 No: 9 Other:3 Other:10 low: 4 Occurrence:6 2,400 Not rep: 3 Frequency: 4 Duration: 2 Peak: 2 independent effect sizes: 9 Number of independent effect sizes: 13 a N the number of participants the effect size is based on which may be smaller than the total number of study participants b Calculated as a weighted average based on number of participants receiving each regimen c High emetic potential 3.0; Low emetic potential <3.0 d Effect size statistically controlled for one or more possible confounding variables e The dependent variable was a combined measure of post-chemotherapy nausea and vomiting f Two separate studies reported in the one article g Combined results for acute and delayed post-chemotherapy nausea h Results reported as non-significant Combined results for three pretreatment nausea expectancy measures Majority of patients (94%) were breast cancer patients k Effect size for intervention group based on pre-intervention assessment only. Effect size for control group based on average of pre- and post assessment i j 8 ann. behav. med. (2010) 40:3 14

ann. behav. med. (2010) 40:3 14 9 were applied in 13 studies and yielded a total of 20 effect sizes. Specific control for the potential moderator of previous history of nausea was conducted in eight of the 17 studies. All studies involved giving at least some patients anti-emetics. All patients received anti-emetics in most studies, and in only two studies there were low usage rates, 3 and 24% [2, 19]. The Association between Expected Nausea and Post-chemotherapy Nausea in All Studies In six of the studies, results were presented for more than one type of dependent variable, and the results were therefore averaged to ensure independence of results. A simple vote count of the 17 independent effect sizes revealed nine statistically significant (p<0.05) results, with the results of the remaining eight studies not reaching statistical significance. As seen in Table 2A, the test for heterogeneity did not reach the chosen statistical significance level (p<0.10), and a fixed effects method was therefore used for analyzing the overall effect of expectancy and post-chemotherapy nausea. This analysis showed a highly significant (p< 0.0001) pooled effect size of ESr=0.18, which corresponds to a Cohen s d [48] of 0.35 and an Odds Ratio (OR) of 2.07, indicating that patients who expected to experience nausea were almost twice as likely to experience postchemotherapy nausea. This result appeared robust, as indicated by the large failsafe number (N=286), which exceeded the suggested criterion (N=95) [49]. Nausea Outcomes We then calculated and compared the pooled effect sizes for each of the three post-chemotherapy nausea assessments methods for which there were three or more independent results. As shown in Table 2B, the 12 studies that had measured severity and the 6 studies that had assessed occurrence of post-chemotherapy nausea yielded similar and highly significant effect sizes of ESr=0.17 and 0.16, respectively. While the results for severity appeared robust with a failsafe number well above the criterion, the results for occurrence was less robust, as indicated by the failsafe number below the criterion. Although the effect size found for frequency of nausea was the highest, ESr= 0.24, it appeared to be the least robust, and a funnel plot indicated a risk of publication bias, which was confirmed by Eggers test (p<0.05). We therefore imputed the missing studies, with Duval and Tweedie s [44] trimand fill and this reduced the effect size from 0.24 to 0.14, which was comparable to the effect sizes found for the other two assessment methods. A Q test revealed that there was no significant difference in effect sizes across the three nausea outcomes. Statistical Control As seen in Table 2C, the nine studies that did not control statistically for any potential confounders yielded a higher pooled effect size (ESr=0.21) than the 13 studies which had controlled for one or more potentially confounding factors (ESr=0.17). This difference, however, did not reach statistical significance. The results for both types of studies appeared robust, and there was no indication of publication bias. In terms of control for a history of nausea in other settings, as seen in Table 2D, the studies that had not controlled for previous nausea history only yielded a slightly higher effect size (ESr=0.20) than studies which had taken this factor into consideration (ESr=0.18). The difference between available studies that did not control for a history of nausea in other settings and those doing so did not reach statistical significance. However, when imputing effect sizes for missing studies to account for potential publication bias in the latter, the resulting effect size was considerably smaller (ESr=0.14). Emetic Potential When analyzing the results of studies of patients receiving chemotherapy with high and low emetic potential, we found a somewhat higher, but less robust, pooled effect size (ESr= 0.23) in the four low emetic potential studies, than in the ten high emetic potential studies (ESr=0.17). As seen in Table 2E, this difference did not reach statistical significance, and furthermore, the result of the low emetic potential studies could be considered less robust, as indicated by the low failsafe number, which was lower than the suggested criterion. The lack of any difference due to emetic potential was also seen in a meta-regression using the average emetic potential score as the predictor of the strength of the association between expectancy and post-chemotherapy nausea (Slope estimate: 0.003; 95% CI: 0.11 to 0.12; p=0.96). Timing of the Assessments As can be seen in Table 2F, the pooled effect sizes for all three combinations of timing of expectancy and postchemotherapy nausea assessments reached statistical significance. The pooled effect size of studies that had assessed the association between expectancy measured before the first infusion with post-chemotherapy nausea measured after the first infusion was somewhat smaller (ESr=0.16) than studies that had assessed the association between expectancy measured before the first infusion and measured nausea after multiple infusions or any infusion other than the first (ESr=0.21). As there was indication of possible publication bias for the latter, missing results were imputed, resulting in an effect size more comparable to that

10 ann. behav. med. (2010) 40:3 14 Table 2 Results of meta-analyses of the influence of nausea expectancy on post-chemotherapy nausea and moderators of the association: nausea outcome, any statistical control, specific control for nausea history, emetic potential, timing of assessments, and cancer type Sample size Heterogeneity a Global effect sizes Failsafe k n Q df p ESr b 95% CI p N c Criterion d A. All studies All studies 17 2,400 17.6 16 0.348 018 e (0.14 0.21) <0.001 286 95 B. Nausea outcome Severity 12 1,757 13.9 11 0.240 0.17 e (0.12 0.21) <0.001 129 70 Occurrence 6 837 5.7 5 0.341 0.16 e (0.09 0.22) <0.001 23 40 Frequency 4 217 9.3 3 0.025 0.24 f (0.01 0.46) 0.043 9 30...(imputed) g 0.14 f ( 0.15 0.40) Between groups h 16 2,348 0.4 e 2 0.84 C. Any statistical control Univariate 9 1,196 8.1 8 0.421 0.21 e (0.15 0.26) <0.001 101 55 Multivariate 13 1,587 15.7 12 0.203 0.17 e (0.12 0.21) <0.001 153 75 Between groups h 17 2,400 0.6 e 1 0.431 D. Control for nausea history No 9 1,309 2.7 8 0.953 0.20 e (0.14 0.25) <0.001 71 55 Yes 8 1,091 14.0 7 0.051 0.18 f (0.09 0.27) <0.001 65 50...(imputed) g 0.14 f (0.03 0.24) Between groups h 17 2,400 0.9 e 1 0.334 E. Emetic potential Low emetic potential 4 266 6.6 3 0.085 0.23 f (0.04 0.39) 0.016 10 30 High emetic potential 10 1,681 10.1 9 0.340 0.17 f (0.13 0.22) <0.001 108 60 Between groups 14 1,947 0.2 e 1 0.629 F. Timing of assessments Expectancy: first 7 1,784 5.2 6 0.513 0.16 e (0.11 0.20) <0.001 57 45 Nausea: first Expectancy: first 7 408 9.0 6 0.175 0.21 e (0.11 0.30) <0.001 30 45 Nausea: other...(imputed) g 0.17 e (0.08 0.26) Expectancy: other 3 260 0.89 2 0.640 0.25 e (0.13 0.36) <0.001 9 25 Nausea: other Between groups 17 2,400 2.49 e 2 0.29 G. Cancer type Breast cancer 8 743 6.5 7 0.485 0.15 e (0.08 0.22) <0.001 28 50... (imputed) g 0.09 e (0.03 0.15) Mixed cancer 8 1,628 8.5 7 0.284 0.18 e (0.14 0.23) <0.001 99 50 Between groups 16 2,371 0.6 e 1 0.46 H. Conservative model Control for nausea history + expectancy measured before 1st infusion 7 1,166 11.8 6 0.066 0.17 f (0.07 0.26) 0.001 40 45 a p<0.10 was taken to suggest heterogeneity b A positive value indicates a positive association between expectancy and post-chemotherapy nausea c Failsafe N number of non-significant studies that would bring the p value to non-significant (p>0.05) d A Failsafe N > criterion (5 k þ 10) indicates a robust result e Fixed effects model f Random effects model g If analyses indicated the possibility of publication bias, missing values were imputed, and an adjusted ESR calculated h To maximize statistical power while ensuring independency of results, results from studies with multiple results were either combined or excluded in the outcome category with the largest number of studies

ann. behav. med. (2010) 40:3 14 11 found for the first type of studies (ESr=0.17). For the third type of study, i.e., the three studies that had measured expectancy before multiple infusions or before any infusion other than the first and assessed nausea after multiple infusions or any infusion other than the first, the effects size was considerably larger (ESr=0.25). The difference between the results of the available studies did not, however, reach statistical significance. Cancer Type As seen in Table 2G, the pooled effect sizes for both studies of breast cancer patients and of mixed samples reached statistical significance. Compared to studies of mixed samples (ESr=0.18), the effect size was smaller for studies of breast cancer patients (ESr=0.15), and even smaller (ESr= 0.09), when imputing results from missing studies due to the indication of publication bias revealed by a funnel plot. The difference between the results of the available studies did not reach statistical significance. Gender The role of gender was explored using meta-regression with the percentage of women in each study as the predictor. The results revealed a negative slope estimate ( 0.20; 95% CI: 0.48 to 0.08), indicating a tendency for the association between expectancy and post-chemotherapy nausea to decrease with increasing percentage of women in the study. However, this tendency was not statistically significant (p=0.16). Conservative Model Finally, we analyzed a conservative model, including only studies that had controlled for history of nausea, and excluding studies that had assessed expectancy prior to one or more other infusions than the first infusion. The results for the seven studies fitting these inclusion and exclusion criteria are shown in Table 2H. The pooled effect size (ESr=0.17) was statistically significant and comparable to the overall effect size (ESr=0.18) found for all 17 studies. The result, however, was less robust, as indicated by the relatively small failsafe number, which did not reach the suggested criterion. Discussion The results of this meta-analysis indicated a robust general positive relationship between expectancies for postchemotherapy nausea and subsequent nausea, indicating that chemotherapy patients who have higher expectancies for nausea are generally more likely to experience postchemotherapy nausea. There did not appear to be any differences in the strength of this association across the different types of nausea measures. This suggests that stronger nausea expectancies are associated with increased occurrence, severity, and frequency of post-chemotherapy nausea equally. As predicted, there was a tendency for weaker associations between expectancy and post-chemotherapy nausea in studies that controlled for at least one potential confounding variable (ESr=0.17) compared with those that did not (ESr=0.21). The was also a tendency for weaker associations between expectancy and post-chemotherapy nausea in studies that specifically controlled for a history of nausea in other settings (ESr=0.18) compared with those that did not (ESr=0.20). Although neither of these differences reached statistical significance, this may have resulted from insufficient power rather than lack of a real difference. This may be particularly so for specific control for a history of nausea, where the analysis indicated possible publication bias in studies controlling for a history of nausea. In fact, when missing results were imputed for studies controlling for a history of nausea, the effect size decreased to 0.14, moving further away from that of studies not controlling for a history of nausea. As mentioned above, one possible explanation for larger effect sizes in studies failing to control for a history of nausea is that stronger nausea expectancies might serve as a marker for higher susceptibility to nausea, rather than actually causing increased postchemotherapy nausea. Also as predicted, there was a tendency toward a stronger association between expectancy and postchemotherapy nausea found in studies measuring expectancies for nausea at more than one infusion or an infusion other than the first compared with those studies assessing nausea expectancies only before the first infusion. As with failing to control for a history of nausea, expectancies measured after the patient had some experience with chemotherapy might simply reflect the patient s knowledge of his/her susceptibility to nausea. This could fully or partially explain the observed association between expectancy and post-chemotherapy nausea. Supporting this, Montgomery and Bovbjerg [20] found that the frequency of nausea over the first five infusions significantly predicted post-chemotherapy nausea after the seventh infusion; however, they also found that expectancy for nausea prior to the seventh infusion significantly predicted postchemotherapy nausea after the seventh infusion even when controlling for frequency of nausea over the first five infusions, suggesting an independent effect of expectancy on post-chemotherapy nausea. There were also trends towards higher effect sizes in studies involving non-breast cancer patients and in studies involving chemotherapy regimens with lower emetic

12 ann. behav. med. (2010) 40:3 14 potential. Again, these differences did not reach statistical significance. However, the imputed effect size to account for possible publication bias in studies involving breast cancer patients (ESr=0.09) was substantially lower than the effect size for mixed cancer patients (ESr=0.18). A possible explanation for this is that breast cancer patients have been found to report higher levels of chemotherapy-induced nausea than patients with other types of cancer, which may result from differences in treatment regimen [16]. As a result, the higher levels of nausea experienced by breast cancer patients could create a ceiling effect whereby, the effect of expectancy on post-chemotherapy nausea is reduced. Similarly, it is possible that chemotherapy regimens with high emetic potential could produce a ceiling effect, which masks the effect of expectancy on nausea and this may explain the trend towards a stronger relation between expectancy and post-chemotherapy nausea in studies involving chemotherapy regiments with low emetic potential. Interestingly, a conservative model that only included studies that measured expectancy before the first infusion and that had specifically controlled for a history of nausea in at least one other setting resulted in an almost identical effect size to the analysis of all studies, ESr=.17, ESr=.18, respectively. The fact that the failsafe number for the conservative model did not quite reach the criterion (40 vs. 45), while the failsafe number for analysis of all studies easily exceeded the criterion (286 vs. 95) could indicate that the effect size in this conservative model was less robust. However, there were only seven studies included in the conservative model compared with 17 in the analysis of all studies, which may account for the failure to reach criterion in the former. Overall, the evidence that cancer patients with stronger expectancies for nausea appear more likely to experience post-chemotherapy nausea appears robust. If this reflects a causal association, i.e., that expecting nausea increases its occurrence, frequency, or severity, then interventions aimed at reducing patient expectancies for nausea should also reduce post-chemotherapy nausea. Although some other non-pharmacological interventions for post-chemotherapy nausea exist, for example relaxation training [50], to our knowledge, only one study to date has employed an expectancy-based intervention. In this study, Shelke et al. [27] randomized first-time chemotherapy patients prescribed the anti-emetic ondansetron to receive either standard information about their treatment (control) or standard information plus specific positive information about the efficacy of ondansetron (intervention). The authors predicted and observed a significant reduction in reported expectancies for nausea in the intervention group from before receiving the information to after receiving it. However, this reduction in reported expectancies did not translate into a reduction in post-chemotherapy nausea. One possible explanation proposed by the authors to account for this was that changing nausea expectancies has no effect on the occurrence of post-chemotherapy nausea. If so, then it would seem that expectancies do not contribute to postchemotherapy nausea and that expectancy-based interventions will be unsuccessful for reducing the burden of chemotherapy-induced nausea. There is, however, an alternative interpretation of Shelke et al. s [27] findings. That is, providing specific positive information about ondansetron may have led to demand characteristics whereby patients reported lower expectancies for nausea after receiving this information, but that their actual expectancies did not change. As a result, it is very difficult to determine whether the intervention was unsuccessful at reducing chemotherapy-induced nausea because expectancies do not contribute to nausea or because the intervention failed to actually reduce patients expectancies for nausea. It is worth noting that expectancy-based interventions have been shown to reduce nausea in areas other than oncology. For example, providing positive information has been found to decrease postoperative nausea following gynaecologic surgery [51] and to protect against seasickness in navel cadets [52]. However, as we have argued previously [10] there are two reasons why expectancybased interventions may be more difficult to implement in cancer patients. First, providing chemotherapy patients with unrealistically low expectancies for nausea, e.g., suggesting that nausea following chemotherapy is unlikely is unethical. Second, patients expectancies are likely to be based on information that they receive from health professionals, family, friends, and the media, as well as their experiences of nausea in other settings and this might mean that simply providing these patients with additional written information about the likelihood of nausea will be insufficient to actually change their expectancies. One way to overcome these problems might be to incorporate a discussion of the patient s expectancies for nausea into the chemotherapy education most patients receive. This would allow the health professional to target and challenge any unrealistically high expectancies for nausea, e.g., believing nausea following chemotherapy is a certainty, thereby avoiding the above ethical concern, and an interactive discussion may be more likely to produce a real reduction in expectancy compared with simply providing the patient with written information aimed at reducing expectancies. In summary, chemotherapy patients with stronger expectancies for nausea appear more likely to experience nausea following their treatment. The positive relationship between expectancies and post-chemotherapy nausea held in a conservative model based on studies that controlled for patients history or nausea and that measured expectancy before the patients first chemotherapy infusion. While this suggests that expectancy-based interventions may be useful

ann. behav. med. (2010) 40:3 14 13 for reducing the burden of post-chemotherapy nausea, the only such study conducted to date [27] failed to achieve this. It is, however, unclear whether this was because expectancies correlate with but do not contribute to postchemotherapy nausea or whether the positive written information provided in the study was insufficient to produce a real reduction in patients expectancies for nausea. To overcome this, future studies should incorporate expectancy-based manipulations that consider the source of the patient s expectancies with the aim of reducing unrealistically high expectancies. These studies should also actively investigate possible moderators of the association between expectancy and post-chemotherapy nausea by investigating if other factors, such as age and anxiety, interact with expectancy as this may highlight patient groups in which expectancy-based interventions could be most effective. 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