Patient Preference and Adherence
`
`Dovepi'w.
`
`ORIGINAL RESEARCH
`
`Patient preferences for important attributes of
`bipolar depression treatments: a discrete choice
`experiment
`
`Th's article was published in the following Dove Press ioumal:
`Patient Preference and Adherence
`
`Daisy Ng-Mak'
`Jiat-Ling Poonz
`Laurie Roberts2
`Leah Kleinman2
`
`Dennis A Revicki2
`
`Krithika Rajagopalan'
`'Global Health Economics and
`Outcomes Research. Sunovlon
`Pharmaceuticals Inc.. Marlborough.
`MA. 2Patient-Centered Research.
`Evidera. Bethesda. MD. USA
`
`Correspondence: Daisy Ng—Mak
`Sunovion Pharmaceuticals Inc.
`84 Waterford Drive. Marlborough
`MA 0| 752. USA
`Tel H 774 369 70|0
`Email daisy.ng-mak@suncwion.com
`
`lubmit m, mamivrpt
`
`9'“
`liltp
`
`'3 In D
`
`Purpose: The purpose ofthis study was to assess patient preferences regard ing pharmacological
`treatment attributes for bipolar depression using a discrete choice experiment (DC E).
`Methods: Adult members of an Internet survey panel with a self-reported diagnosis of bipolar
`depression were invited via email to participate in a web-based DCE survey. Participants were
`asked to choose between hypothetical medication alternatives defined by attributes and levels
`that were varied systematically. The six treatment attributes included in the DCF. were ti me to
`improvement, risk of becoming manic, weight gain. risk of sedation, increased blood sugar, and
`increased cholesterol. Attributes were supported by literature review. expert input. and results
`of focus groups with patients. Sawtooth C BC System for Choiee-Bascd Conjoint Analysis was
`used to estimate the part—worth utilities for the DCE analyses.
`Results: The analytical sample included 185 participants (50.8% females) From a total of
`200 participants. The DCF. analyses found weight gain to be the most important treatment attri-
`bute (relative importance =49.6%i, followed by risk ofacdation (20.2%). risk ofmania ( [10%).
`increased blood sugar (83%), increased cholesterol (5.2%). and time to improvement (3.7%).
`Conclusion: Results from this DCE suggest that adults wrth bipolar depression considered
`risks of weight gain and sedation associated with pharmacothcrapy as the most important attri-
`butes for the treatment of bipolar depression. incorporating patient preferences in the treatment
`decision-making process may potentially have an impact on treatment adherence and satisfaction
`and. ultimately. patient outcomes.
`Keywords: bipolar depression, treatment preference, adverse events, weight gain
`
`Introduction
`
`Bipolar l disorder is charactcri zcd by periods of severe mood episodes that fluctuate
`between clinical depression. mania, and mixed episodes and are associated with sig-
`nificant disability and functional impairment.‘ In the US. the lifetime prevalence of
`bipolar l disorder is 1%. with a l 2-month prevalence oi‘0.6%.2 Patients diagrosed with
`bipolar l disorder have been found to experience depressive symptoms three times
`more ofien than manic symptoms.-‘-" Dcprcssivc episodes in bipolar disorder( ic. bipolar
`depression) tend to last longer. occur more frequently. and are associated with higher
`suicide rates and work-related disability compared to manic episodes“
`Although several treatment options are available for the management of bipolar l
`disorder. there are currently only three US Food and Drug Administration (F DA)-
`approved atypical antipsychotic treatments for bipolar depression: quctiapinc.
`olanzapine in combination with fluoxetine. and lurasidone.“ These medications have
`also received regulatory approval for the treatment of bipolar depression in other
`
`35
`Patient Preference and Adherence 20l8: l 2 3544
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`Ng—Mak at al
`
`Dover-um
`
`localities such as Canada (lurasidone and quetiapine). the
`European Union (quetiapine), and Japan (olanzapine). As a
`class. atypical anti psychot ics have unique efficacy and toler-
`ability profiles but are usually associated with considerable
`adverse effects. including weight gain, type 2 diabetes, and
`hyperlipidemia.7
`Approximately 60% of patients with bipolar disorder
`do not sufficiently adhere to their medication" “ Accord-
`ing to a recent systematic literature review of observational
`studies. one of the most commonly reported reasons for
`medication nonadhercnce in bipolar disorder is adverse
`effects of treatment. such as weight gain. sedation. tremors.
`and perceived cognitive impairment.”-” lnaddition. residual
`depressive symptoms may also negatively impact medica-
`tion adherence.“ Using a stated-preference approach. side
`effects of weight gain or cognitive impairment were similarly
`identified as major considerations for the treatment of non-
`adhercnce in bipolar disorder. ‘5 The management of bipolar
`disorder includes proactive monitoring of these adverse
`effects. such as weight gain. through encouragement of
`lifestyle and behavioral modifications."
`Treatment nonadhercnce in bipolar disorder remains
`a continuous challenge with both clinical and economic
`consequences.“ "' 7 Nonadherence is associated with decreased
`treatment effectiveness. increased relapses. escalated mor-
`bidity. and increased hospitalizations and other health care
`utilization.”'”'"' which can lead to higher health care costs
`and decreased quality of life. Identifying patient treatment
`preferences by allowing patients to trade-offthe benefits and
`risks associated with the treatment of bi polar depression may
`lead to a better understanding of the patients‘ perspective
`for both physicians and patients and. ultimately. increase
`medication adherence rates.”
`
`One way to assess patient preferences is to conduct
`a discrete choice experiment (DCE). a methodology that
`resembles real-life decision making. "' In a DCE. participants
`are asked to choose between scenarios describing realistic
`treatment options and where they make trade—offs between
`difierent treatment attributes. This differs fiom a survey-only
`approach where patients may be asked to answer questions
`about independent treatment features. including side effects.
`without taking into account the trade-offs required to choose
`between multiple treatment characteristics at once.
`A few published studies of DCEs were conducted in
`mental health populations. However. a previous research has
`found that patients with severe mental illness. such as schizo-
`phrenia or major depressive disorder. may be able to appro-
`priately complete DCF. tasks and make meaningful decisions
`
`36
`
`mumn mun-am c
`you
`a
`Dover w
`
`about preferred treatment scenarios based on different
`attributes.” DCE methodology has previously been used in a
`bipolar disorder population to assess factors associated with
`nonadhercnce to treatment. The results demonstrated that
`
`patients were more likely to be adherent to medications ifthey
`reduced the severity oftheir depressive episodes and did not
`cause weight gain or cognitive side effects." However. this
`prior work did not focus on bipolar depression.
`The objective of this study was to assess patient prefer-
`ences regarding pharmacological treatment attributes for
`bipolar depression via a DCE.20
`
`Methods
`
`The DCE involved a series of systematic steps. including
`1 ) development oftreatment attributes, and 2t implementation
`of the DCE. All study activities were conducted in English.
`
`Development of treatment attributes
`Relevant treatment attributes and conceptual i7ations oftreat-
`ment scenarios were developed through literature reviews
`and focus groups. A targeted literature review of articles
`that described bipolar depression treatments and a review
`of recent product inserts were conducted. PubMed and
`Embase were used to conduct the literature search. and the
`
`search strategies are included as a supplement to the manu-
`script. Product inserts for 29 medications used to manage
`bipolar disorder/depression were reviewed. including nine
`typical antipsyehoties.
`l2 atypical antipsyehoties. seven
`anticonvulsants. and lithium. Information related to dosing
`characteristics. need for monitoring. efficacy (cg. time to
`improvement. remission rates). adherence rates. and common
`adverse events was extracted from these review sources.
`
`Following the literature review. one expert clinician
`interview and two focus groups with 16 adult patients“
`were conducted. The purpose of the expert interview was
`to draw on the clinician‘s experiences to identify key issues
`and concerns in bipolar depression. with a greater emphasis
`on treatment side effects and reasons for continuing or dis-
`continuing treatment. The interview was condueted using a
`semi-structured interview guide.
`The focus groups enrolled adult participants from two
`clinical sites in the US (n=8 per site). All focus group par-
`ticipants had a clinician-confirmed diagnosis of bipolar l
`disorder. a history of 21 major depressive episode within
`the last 12 months.a lifetime history of El manic or mixed
`manic episode. and currently or previously received antipsy-
`chotic drug therapy for bipolar disorder. Mean age of focus
`group participants was 47.9 years (SD 26.0 years). and
`
`Patient Preference and Adherence 20|82 I 2
`
`

`

`Doveiv
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`Patient preferences for the treatment of bipolar depression
`
`69% were females. Mean time since the participants' initial
`bipolar I disorder diagnosis was 15.7 years ( 50:1 1.4 years).
`and their mean duration of atypical antipsychotic use was
`4.9 years (SD =4.7 years). The focus groups were conducted
`using a semi-structured interview guide to elicit information
`regarding expectations of treatment. treatment experiences.
`and potential barriers to treatment for bipolar depression.
`Audio recordings of the focus groups were transcribed and
`analyzed for themes that patients described as being related
`to their expectations and preferences for bipolar depression
`treatment using ATLAS.ti (version 7.5.3).
`The most important medication attributes identified from
`the expert clinician interview and patient focus groups are
`given in Table 1. Efficacy and weight gain were reported
`as important treatment attributes for patients with bipolar
`depression. Patients also defined “time to improvement”
`as the time from treatment initiation to when they began to
`observe improvements in their symptoms. Findings from
`the qualitative research were used to determine the relevant
`attributes and attribute levels for the DCE scenarios to be
`
`used in the pilot and main DCE studies. In determining the
`fiml list of attributes. greater emphasis was placed on factors
`identified by patients as being important in influencing their
`treatment decisions. Levels of attributes were determined
`
`based on results of clinical trials reported in the product
`inserts, including incidence rates of each event and time to
`improvement of depressive symptoms.
`
`Implementation of DCE
`The DCE was implemented via a one-time. cross-sectional.
`web-based survey. Prior to full implementation, one-on-one
`pilot interviews were conducted via web conference.
`
`Participants
`For the pilot and main web-based surveys. members of
`MedPanelE2 an Internet survey panel. with self-reported
`bipolar depression were invited via e-mail to participate.
`
`Table I Important mediation attributes for the treatment of
`bipolar depression identified via interviewsa
`
`Expert clinician
`Patlent focus groups
`Efficacy
`Efficacy
`Metabolic side effects
`Increased blood sugar
`Sedation
`Increased cholesterol
`
`Sexual dysfunction
`Weight yin
`
`Note: ‘Hedcwon atu'lbuls are listed alphabetically.
`
`Risk of becoming manic
`Sedation
`Time to improvanent
`Weight gain
`
`MedPaneI speciali7es in the life science industry and main-
`tains a large patient panel across various diseases. includ-
`ing bipolar disorder. MedPanel members were originally
`recruited through patient associations. patient support groups.
`and physician referrals. Interested patients answered a series
`of screening questions to determine study eligibility.
`Inclusion criteria were adult subjects ( 18—75 years). self-
`reponed diagnosis of bipolar depression (bipolar I disorder
`with most recently documented depressive episode within the
`last 12 months), lifetime history of 21 manic or mixed manic
`episode, and currently or previously received ant ipsychotic
`drug therapy for bipolar disorder. Exclusion criteria were hos-
`pitalization for a manic or mixed episode within the 60 days
`prior to screening. participation in any other clinical trial. or
`had received study medication S45 days from study screen-
`ing. Diagnosis of bipolar depression was self-reported by
`patients. and symptoms of depression were further verified
`through patients‘ responses to screening questions related to
`use of medications to manage bipolar disorder and symptoms
`of depression and/or mania.
`Institutional review board approval was obtained from
`Ethical and Independent Review Services on October 16.
`2015 (study number: 15127-01) for the study protocol and
`recruitment materials. All participants provided electronic
`infon‘nod consent. and each eligible participant received 520
`for completing the study.
`A pilot study with four participants was conducted using
`the preliminary DCE scenarios to assess the clarity and
`understanding of the web-based survey questions. Based
`on partieipants' feedback. minor changes were made to the
`attribute names and the order of tasks. Participants under-
`stood the DCE task and were able to complete the web-based
`survey with minimal difficulty. The final treatment attri butcs
`and levels used for the DCE scenarios are given in Table 2.
`In the main DCE. eligible participants cotnplctcd only the
`web-based survey.
`
`Survey instrument
`Eligible participants were asked to complete up to 10 sets of
`DCE scenarios, soc iodemographic and clinical questions, the
`self-reported Montgomery—Asberg Depression Rating Scale
`(MADRS-Sfi-‘J‘ the WHO-5 Well-Being Index ( WHO-5),25
`and the Patient-Reported Outcomes Measurement Informa-
`tion System (PROMIS) Global Health Instrument (CHI)?
`In each DCE scenario. two hypothetical bipolar depres-
`sion medications comprising different attributes (time to
`improvement. risk of becoming manic. weight gain. risk of
`mdation. increased blood sugar. and increased cholesterol)
`
`Patient Preference and Adierence 2018:12
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`min-m yew rII-tuvuipt
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`

`Ng—Mak et al
`
`Table 2 Final DCE attributes and levels
`
`Dovepzm
`
`Attribute
`Time to
`improvement
`
`Risk of becoming
`manic
`
`Description
`The time will you leel an Improvement in you
`depressive symptoms (ie. sadness. trying, leeling
`of isolation) after you start taking the medication
`The chance that taking the medication when you
`are in a depressive episode will uuse you to
`become manic instead
`
`Weight gain
`
`The amount of weight gain you will experience
`after taking the medication
`
`Levels
`i week
`2 weeks
`4 weeks
`Fewer don one in IN of depressed patients will switch to
`being inmic after taking the medication
`Five in it!) of depressed patients will switch to being manic
`alter takirg the medication
`Elgit in I00 oi deprssed patients will switch to being
`maic alter taking the medication
`Patients experience a minimtm weigit gain of less than
`3|; after taking the medication
`Patiems experience an average weight gain of 3—lO lbs after
`taking the medication
`Patients experiaice an average weight gain oi l0—20 lbs
`after takirg the medication
`Patients experience an average weight gain of more than
`20lbs after taking the medication
`Fewe- than l0 in mo of patients will experience excessive
`sleepinew or drowsiness after taking the mediation
`I0—24 in lOO patients wil experience exca-ve sleepiness
`or drowsiness after taking the medication
`25—50 in l00 patients will experience excessive slapiness
`or drowsiness after taking the medication
`More than 50 in |00 patients will experience excessive
`
`sleepiness or drowsiness after talong the mediation
`Fewer than live in IOO patients will experience increased
`blood sugar (glucose) after taking the medication
`lO—l S in l00 patients wll experience increased blood sugar
`(glucose) after taking the medication
`Fewa that live in I00 patients will experience increased
`cholesterol levels after taking the medication
`I0-l S in IOO patients will experience increased cholesterol
`levels after taking the medication
`Abbreviation: DCE. discrm choice experiment.
`
`Risk of sedation
`
`The chance that you will eqaei’ience excessive
`sleepiness or drowsmess after taking the
`medication
`
`Increased blood
`sugar (glucose)
`
`The chance that you- blood sugar (glucose) levels
`will change from normal to high after taking the
`medication
`
`Increased cholesterol
`(fat in the blood)
`
`The chance that cholesterol levels wil change
`from normal to high after takirg the medication
`
`and corresponding levels for each attribute were presented
`(Table 2 and Figure 1). Participants were instructcd to review
`the treatment pairings and select the medication they would
`prefer to take at the present time given the options. Each
`participant responded to only 10 choice pairs in order to both
`minimize the cognitive burden on participants and maximize
`the efficiency of the study design. given the number of attri-
`butes and levels included in the DCE. One of the discrete
`
`choice scenarios presented was a fixed-choice question and
`was not includcd in thc final analysis. The fixed-choice
`question presented a clearly favorable medication choice to
`establish that participants understood the DCE task. Those
`who responded incorrectly were excluded from the analysis.
`To prevent potential biases in responses. the fixed-choice
`question was presented as part of the full set of scenarios.
`In addition to the discrete choice task. participants were also
`asked to directly rank the six attributes in order of importance
`on a scale of 1 (most important) to 6 (least important).
`
`The MADRS-S is a nine-item self-report scale assessing
`dcprcssivc symptoms over the past 3 days?“ Patients were
`asked to rate the severity ofeach of the symptoms assessed on
`a scale ranging from 0 to 6. The total score for the MADRS-S
`was then calculated by summing the ratings ofthc nine items.
`which ranged between 0 and 54. with higher scores indicating
`greater impairment.
`The WHO-S is a measure ofemotional well—being devel—
`oped from the World Health Organization-Ten Well—Being
`index” and consists of five positively worded itcms assessing
`emotional well-being over the past 2 weeks. Each item is
`rated ona 6-point Likert scale ranging from 0 (not present) to
`5 (constantly present). individual item ratings arc summed to
`obtain a raw score ranging from 0 (worst possible quality of
`life) to 25 (best possible quality of life). which may be trans-
`formed into a percentage score ranging from 0 (worst possible
`quality of life) to 100 (best possible quality of life). A raw
`score 513 has been found to be indicative of depression.
`
`38
`
`submit your nun-amp.
`Dawn ‘-
`
`Patient Preference and Adherence 20|8zl2
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`

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`Davey
`
`Patient preterences tor the treatment of bipolar depression
`
`Now keeping in mind the features you just read through, please read each option carefully and Choose Wthh medication you would prefer '0! the treatment Of your bipolar depression.
`
`Ifyou need to review the description of the medication features again. click here; Glossary
`
`Time to improvement
`
`Risk oi becoming manic
`
`“'9” 93'"
`
`Risk ot sedation
`
`Increased blood
`sugar (9|
`)
`
`Increased cholesterol
`
`Four weeks
`Leesthm 1% (leverthan 1 In 100w
`depressed patients will which to being manic
`alter taking the nucleation.
`
`Patients experience an average weight gain
`or 10-20 lbs otter taking the medication.
`Leee than 10% (tewerthan 10 In 100) of
`patients wtl experience enceaeive sleepiness
`or dominoes alter taking the medledion.
`Lesslhmm (fewerfllantlin 100)of
`patients will experience increased blood
`
`sugar (glucose) after taking the medication.
`
`101.46% (to to 16 in 100) of patierta wit
`experlence Increased cholesterol levels
`afler taking the medication.
`
`Four weeiie
`
`8% (a In 100) of depressed patients wIl
`switch to being maria aler taking the
`medication.
`
`levels otter taking the medication.
`
`Patients experience an average weight gain
`of 10-20 lbs otter taking the medication.
`
`asst—sou (26 to ‘0 in 100) ct patientewll
`experience excessive deepineas or
`«whose after taking the medication.
`Less than 0% (m than I in 100) of
`patients will experience hcreaeed blood
`sugar (glucose) atler taking the medication
`Lesa than 6% (tevrerthan 6 in 100) of
`patients will experlence Increased cholesterol
`
`Figure I DCE question sample.
`Abbreviation: DCE. durae choice experiment.
`
`The PROMIS Global Health Questionnaire:6 comprises
`10 questions covering the global domains of physical health
`and mental health. Severity questions assess the respondent‘s
`current state using a response scale of “excellent. very good.
`good. fair. and poor". Frequency questions assess the past
`7 days using a response scale of “never. rarely. sometimes.
`oficn. and always”.
`
`Statistical analyses of DCE
`Descriptive analyses were conducted on sociodemographic
`
`and patient-reported outcome questionnaire data. For the
`DCE data. prcfcrcncc weights (part-worth utility values) were
`estimated using a random—effects multinomial logit model.27
`The model estimated the probability of a patient choosing
`an alternative 1' (over a set of possible alternatives I in the
`given choice set) with the Bs representing the estimated
`part-worth utilities.
`
`Exp (V(B.X' ll
`I: = ,—-
`21:. Exp max,»
`
`were scaled to have a mean value of zero and then used to
`
`calculate the relative importance of each attribute. The rela-
`tive importance of each attribute was then calculated using
`the following formula:
`
`Relative importance : Ovcrall utility for each attribute
`Total utility
`
`Overall utility value for each attribute equaled the range
`of part-worth utilities within each attribute. and total utility
`value equaled the sum ofoverall utility values across all attri-
`butes. The relative importance ofeach attribute was expressed
`as a percentage. reflecting the proportion ofthe variance in the
`overall medication decision that was accounted for by each
`attribute. Utilities and relative importance were evaluated for
`each DCE attribute. Sawtooth CBC System for Choice-Based
`Conjoint Analysis (version 7: Sawtooth Soflwarc. Inc.. Provo.
`Utah. USA) was used to generate the DCE survey questions
`and to cstiinatc thc pan-worth utilities for the DCE analyses.
`SAS statistical software version 9.4 [SAS Institute lnc.. Cary.
`NC. USA) was used to conduct all other analyses.
`
`A positive part-worth utility indicated that the attribute
`level was preferred over levels with negative values. and
`larger part-worth utilities indicated a higher degree of pref-
`crcncc for one level ovcr another. The part-worth utilities
`
`Subgroup analyses
`Participant preferences were stratified by gender and age
`(using a median split l. The subgroups were determined based
`on a priori hypotheses that there may be gender differences
`
`Patient Preference and Adierence 2O |8:| 2
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`mun-2i yew Illaiuluip‘
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`Ng—Mak at al
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`DOVQ;~:- \\
`
`in preferences for the attributes included in the DCE. espe-
`cially weight gain. In addition, it was hypothesized that older
`patients may be diagnosed as bipolar for longer and have
`more experience with different bipolar medications. while
`younger patients may place a greater emphasis on attributes
`such as risk of sedation due to work or school productivity
`concerns. Relative importance was calculated separately
`
`for each age and gender subgroup. Chi-square tests were
`used to determine any significant differences in the relative
`importance of the attributes between subgroups.
`
`Results
`
`Sample characteristics
`A total of 200 eligible participants provided informed con-
`sent and completed the main web-based DCE survey. In all.
`1 1 ( 5.5%) participants provided an incorrect response to the
`fixed-choice question and four participants (2.0%) “straight-
`lined" their responses (ie, they selected the same response
`option for all questions. indicating that they may not have
`been making decisions but instead trying to complete the
`survey quickly); these participants were excluded from
`the analyses. resulting in 185 participants being included in
`the analytical sample.
`Demographic and self-reported clinical characteristics of
`the participants are presented in Table 3. The majority of the
`participants (88.6%) were currently receiving medication for
`bipolar depression. most commonly atypical antipsyehotics
`(75.1%). Mean MADRS-S total score was 23.9 (SD =99).
`
`indicative of moderate depression. and mean WHO-5 raw
`score was 8.9 (SD =5.0). indicative of poor well-being.
`Physical health ('T-score :39. 1; SD :72) and mental health
`(T-score =35.6; SD =7.7) scores. as assessed by the PROMIS
`GHI. were lower than that of the general population (based
`on the standardized population mean of 50). also indicating
`poor health status?"
`
`Relative importance weights for
`treatment attributes
`
`The part—worth utility values are shown in Figure 2. The cor—
`responding relative importance indicated that. in the context
`of the included attributes. participants considered weight
`gain as the most important attribute of a treatment (relative
`importance =49.6%: Figure 2). A treatment associated with
`less weight gain was preferred over a treatment associated
`with more weight gain. In the context of this study. the
`second-most important attri bute was risk of sedation (relative
`importance =20.2%). Treatment associated with lower risk
`of sedation was preferred over treatment with more sedation.
`
`‘0
`
`.uumri yvuv nr‘nuhnpl
`Davey .
`
`3 (LG)
`4 (2.2)
`l3 (7.0)
`ISB (85.4)
`I (0.5)
`6 (3.2)
`
`42 (22.7)
`I43 (77.3)
`
`l24 (67.0)
`6| (33.0)
`
`64 (34-6)
`56 (30.3)
`24 ( I3.0)
`I9 (I03)
`9 (4.9)
`l3 (7.0)
`
`[39 (75.l)
`96 (5L9)
`
`2| (I L4)
`38 (20.5)
`
`23.9 (9.9) [24. 2—50]
`
`35.7 (I99) [32. 0—84]
`
`Table 3 Demographic and self-reported clinical characteristics of
`DCE web-based survey participants
`Characteristic
`
`N=l85
`
`4L7 (I14) [IS—71]
`94 (50.8)
`
`Age. years. mean (SD) [nrge]
`Gender. female. n ('6)
`Race/ethnicity. n (9Q)
`American Indian or Alaska Native
`Nian
`Black or Alrican American
`White
`Others‘
`More than one‘
`Current living/domestic situation. it (96)
`Living alone
`Living with others (including friends.
`partner. parents. other family)
`Education. n (‘34)
`Some college and below
`College degree and above
`Household income. n (‘96)
`<$20.ooo
`$20.00 |-$40.000
`$40.00 |—$60.000
`$60.00 |—$80.(XX)
`$80.00 I45 I 00.000
`>SIOOJIXJI
`Current treatment for bipolar depressron.‘ n (3;)
`Atypical antipsychotlt:
`Non-atyplml antipsychoucs
`(cg. antidepressants. mood stabilizers.
`anticonvulsnts. stimdants)
`None
`Prior or cu‘rent treatment with SSRI: or
`SNRIs, n (as)
`MADRS-S total score. mean (SD) [median
`range]
`WHO-5 total percentage score. mean (SD)
`[median. rarge]
`PROMIS global health sale. mean (SD)
`[median urge]
`39.| (7.2) [39.8. 20—58]
`Physical health summary T-score
`Mental halth summary T-score
`35.6 (7.7) [36.3. 2: -63]
`2.7 (0.9) [3.
`I—5]
`General health
`2.2 (LO) [2.
`I—5]
`Social health
`Notes: 'Other race referred to Marian ‘Mdu'ple races were sdected: Indan/
`Alaska Native and \M'rira. ‘Respomes are not mutually exclusive.
`sdi-reported
`Abbreviuh'om: DCE. discrete choice
`experiment: HANS-S.
`Montgomery—Asher: Depression Rating Scale: PROHIS. Patient-Reported Outcomes
`Neutron-ant Mei-matron System: SNRl remn‘mnoropinaplrrine [Wink-“mt
`SSRI. selective serotonin rawhinhibitor: WHO~5. VVHO-S WeI-Beirg Index
`
`The remaining attributes. in order of relative importance.
`were risk of becoming manic. increased blood glucose.
`increased cholesterol. and time to improvement. Part-worth
`utilities were in the expected direction for the levels within
`each ofthese attributes. with greater preference for less severe
`adverse events and faster improvement.
`Participant preferences were further stratified by gen-
`der and age (using the median split of 540 years [n=93]
`
`Patient Preference and Adherence 20|8: I 2
`
`

`

`Dove;~
`
`150
`
`125
`
`425
`
`—175
`
`Patient prelemnces for the treatment at bipolar depression
`
`3-10lbs
`
`
`
`10-20lbs
`
`Leathan3lbs
`
`
`
`Morethan20lbsrv-I
`
`
`
`Fmrthan10in100
`
`10-24in100
`
`25—50in100
`
`
`
`Morethan50In100
`
`Fewerthan1in100
`
`5In100
`
`Bin100
`
`10—15in100
`
`Fowarthan5In100
`
`
`
`Fewerthan5in100
`
`10—15in100
`
`1week
`
`Zweelts
`
`tweaks
`
`wag-it gatn
`(RI new.)
`
`Rlsk ol sedatlon
`(RI =20.2’/.)
`
`Rlslt 01 becoming
`manic
`(RI =1 3.0%)
`
`Increased ‘ Increased
`blood sugar cholesterol
`(R! 23.3%)
`(RI =6.2%)
`
`Tune to
`Improvement
`(RI =3.7%)
`
`Flgurez I’m-worth utility values (N=l85)
`Notes: Part-worth utiity talus scaled within each attribute to have a mean of (1 Positive (art-worth utility due indicates that the attribute levd is prelerred over levels
`will negative vaiuee. Larger part-worth uu'lity values indicate I higher degree oi preference for one level over another. Error bars denote standard errors
`Abbreviation: RI. relative impenance
`
`and >40 years [n=92]). Within each subgroup, the relative
`importance of each attribute in rank order was the same as
`that of the overall sample. Descriptively. females placed
`greater relative importance on weight gain (53.2%) than
`males (45.9%). while slightly greater relative importance
`was placed on all other attributes by males than by females.
`The attributes “i ncrcascd cholesterol” and “ti me to improve-
`ment” were both fifih in relative importance in thc >40 years
`subgroup. A chi-square test comparing relative importance
`between subgroups ( male vs female. 540 years vs >40ycars)
`found no statistically significant differences in the relative
`importance of each attribute across gender or age groups.
`When asked to directly rank the six attributes included
`in the DCE in order of importance (1: most important; 6:
`least important). the participants ranked weight gain as the
`most important. with a mean rank of 2.4 (SD =1 .6). followed
`by risk of becoming manic (mean rank =3.0 [SD =l.7]).
`time to improvement (mean rank =3.l [SD =l.6]). risk of
`sedation (mean rank =3.7 [SD =1 .7]). increased blood sugar
`(mean rank :42 [SD :1 .4]). and increased cholesterol (mean
`rank 24.6 [SD :1 .3]).
`
`Discussion
`
`This is the first study to examine patient preferences in the
`treatment of bipolar depression using a DCE methodology.
`In this DCE study. weight gain. risk of sedation. and risk of
`becoming manic were identified as the three most important
`attributes for adult participants with bipolar depression.
`In contrast. when time to improvement was considered along-
`side these side effects. it was ranked the least important. These
`findings were consistent across age and gender subgroups.
`While this study was not designed to assess factors that would
`increase patients' adherence to treatment. it identified factors
`that patients consider important in influencing their treatment
`decisions. These factors can be used by health care provid-
`ers as a starting point to initiate treatment discussions. and
`discussions around treatment adherence. with patients.
`The importance of tolerability in influencing patient
`treatment preferences emerges as a consistent theme when
`examining the results of this study with other studies con-
`ducted in mental health populations using DCE methodol-
`ogy. including bipolar disorder. major depressive disorder.
`and schizophrenia.‘““3“" Consistent with the literature.
`
`Patient Preference and Adierence 20 IS: I 2
`
`nahmil m, rII-Iuwipt
`
`4|
`
`

`

`Ng—Mak at al
`
`DOVE;~:- \\
`
`our findings demonstrated that tolerability in general. and
`weight gain in particular, is an important treatment attribute
`for patients with bipolar disorder or bipolar depression. ”-3133
`As weight gain among patients taking atypical antipsychotics
`is a major concern, a personalized treatment with a relatively
`lower risk of weight gain may increase treatment adherence
`and thereby improve patient outcornes.”"’
`Risk of sedation was identified as the second most impor-
`tant treatment attribute ofthis study. As study partic i pants were
`generally younger. they may be more concerned about bipolar
`depression treatments with sedative effects, which might
`impair normal activities of daily livingand work productivity.
`Research suggests that sedation may not only have a significant
`impact on patients’ quality oflife. and social and occupational
`functioning. it can also cause impaired cognitive and motor
`
`functioning." which might heighten the risk of accidents.”
`Not surprisingly. Mago et al'-‘ identified risk of sedation as a
`reason for treatment discontinuation in up to 30% of bipolar
`disorder patients. In addition, sedation and weight gain were
`ident