{"title":"多基因药物基因组测试,包括决策支持工具,指导药物选择严重抑郁症:健康技术评估。","authors":"","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Major depression is a substantial public health concern that can affect personal relationships, reduce people's ability to go to school or work, and lead to social isolation. Multi-gene pharmacogenomic testing that includes decision-support tools can help predict which depression medications and dosages are most likely to result in a strong response to treatment or to have the lowest risk of adverse events on the basis of people's genes.We conducted a health technology assessment of multi-gene pharmacogenomic testing that includes decision-support tools for people with major depression. Our assessment evaluated effectiveness, safety, cost-effectiveness, the budget impact of publicly funding multi-gene pharmacogenomic testing, and patient preferences and values.</p><p><strong>Methods: </strong>We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane Risk of Bias Tool and the Risk of Bias Assessment Tool for Nonrandomized studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria.We performed a systematic literature search of the economic evidence to review published cost-effectiveness studies on multi-gene pharmacogenomic testing that includes a decision-support tool in people with major depression. We developed a state-transition model and conducted a probabilistic analysis to determine the incremental cost of multi-gene pharmacogenomic testing versus treatment as usual per quality-adjusted life-year (QALY) gained for people with major depression who had inadequate response to one or more antidepressant medications. In the reference case (with GeneSight-guided care), we considered a 1-year time horizon with an Ontario Ministry of Health perspective. We also estimated the 5-year budget impact of publicly funding multi-gene pharmacogenomic testing for people with major depression in Ontario.To contextualize the potential value of multi-gene pharmacogenomic testing that includes decision-support tools, we spoke with people who have major depression and their families.</p><p><strong>Results: </strong>We included 14 studies in the clinical evidence review that evaluated six multi-gene pharmacogenomic tests. Although all tests included decision-support tools, they otherwise differed greatly, as did study design, populations included in studies, and outcomes reported. Little or no improvement was observed on change in HAM-D17 depression score compared with treatment as usual for any test evaluated (GRADE: Low-Very Low). GeneSight- and NeuroIDgenetix-guided medication selection led to statistically significant improvements in response (GRADE: Low-Very Low) and remission (GRADE: Low-Very Low), while treatment guided by CNSdose led to significant improvement in remission rates (GRADE: Low), but the study did not report on response. Results were inconsistent and uncertain for the impact of Neuropharmagen, and no significant improvement was observed for Genecept or another unspecified test for either response or remission (GRADE: Low-Very Low). Neuropharmagen may reduce adverse events and CNSDose may reduce intolerability to medication, while no difference was observed in adverse events with GeneSight, Genecept, or another unspecified test (GRADE: Moderate-Very Low). No studies reported data on suicide, treatment adherence, relapse, recovery, or recurrence of depression symptoms.Our review included four model-based economic studies and found that multi-gene pharmacogenomic testing was associated with greater effectiveness and cost savings than treatment as usual, over long-term (i.e., 3-,5-year and lifetime) time horizons. Since none of the included studies was fully applicable to the Ontario health care system, we conducted a primary economic evaluation.Our reference case analysis over the 1-year time horizon found that multi-gene pharmacogenomic testing (with GeneSight) was associated with additional QALYs (0.03, 95% credible interval [CrI]: 0.005; 0.072) and additional costs ($1,906, 95% Crl: $688; $3,360). An incremental cost-effectiveness ratio was $60,564 per QALY gained. The probability of the intervention being cost-effective (vs. treatment as usual) was 36.8% at a willingness-to-pay amount of $50,000 per QALY (i.e., moderately likely not to be cost-effective), rising to 70.7% at a willingness-to-pay amount of $100,000 per QALY (i.e., moderately likely to be cost-effective). Evidence informing economic modeling of the reference case with GeneSight and other multi-gene pharmacogenomic tests was of low to very low quality, implying considerable uncertainty or low confidence in the effectiveness estimates. The price of the test, efficacy of the intervention on remission, time horizon, and analytic perspective were major determinants of the cost-effectiveness results. If the test price were assumed to be $2,162 (compared with $2,500 in the reference case), the intervention would be cost-effective at a willingness-to-pay amount of $50,000 per QALY; moreover, if the price decreased to $595, the intervention would be cost saving (or dominant) compared with treatment as usual.At an increasing uptake of 1% per year and a test price of $2,500, the annual budget impact of publicly funding multi-gene pharmacogenomic testing in Ontario over the next 5 years ranged from an additional $3.5 million in year 1 (at uptake of 1%) to $16.8 million in year 5. The 5-year budget impact was estimated at about $52 million.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side effects and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.</p><p><strong>Conclusions: </strong>Multi-gene pharmacogenomic testing that includes decision-support tools to guide medication selection for depression varies widely. Differences between individual tests must be considered, as clinical utility observed with one test might not apply to other tests. Overall, effectiveness was inconsistent among the six multi-gene pharmacogenomic tests we identified. Multi-gene pharmacogenomic tests may result in little or no difference in improvement in depression scores compared with treatment as usual, but some tests may improve response to treatment or remission from depression. The impact on adverse events is uncertain. The evidence, however, is uncertain, and therefore our confidence that these observed effects reflect the true effects is low to very low.For the management of major depression in people who had inadequate response to at least one medication, some multi-gene pharmacogenomic tests that include decision support tools are associated with additional costs and QALYs over the 1-year time horizon, and maybe be cost-effective at the willingness-to-pay amount of $100,000 per QALY. Publicly funding multi-gene pharmacogenomic testing in Ontario would result in additional annual costs of between $3.5 million and $16.8 million, with a total budget impact of about $52 million over the next 5 years.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.</p>","PeriodicalId":39160,"journal":{"name":"Ontario Health Technology Assessment Series","volume":"21 13","pages":"1-214"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382305/pdf/ohtas-21-13.pdf","citationCount":"0","resultStr":"{\"title\":\"Multi-gene Pharmacogenomic Testing That Includes Decision-Support Tools to Guide Medication Selection for Major Depression: A Health Technology Assessment.\",\"authors\":\"\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Major depression is a substantial public health concern that can affect personal relationships, reduce people's ability to go to school or work, and lead to social isolation. Multi-gene pharmacogenomic testing that includes decision-support tools can help predict which depression medications and dosages are most likely to result in a strong response to treatment or to have the lowest risk of adverse events on the basis of people's genes.We conducted a health technology assessment of multi-gene pharmacogenomic testing that includes decision-support tools for people with major depression. Our assessment evaluated effectiveness, safety, cost-effectiveness, the budget impact of publicly funding multi-gene pharmacogenomic testing, and patient preferences and values.</p><p><strong>Methods: </strong>We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane Risk of Bias Tool and the Risk of Bias Assessment Tool for Nonrandomized studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria.We performed a systematic literature search of the economic evidence to review published cost-effectiveness studies on multi-gene pharmacogenomic testing that includes a decision-support tool in people with major depression. We developed a state-transition model and conducted a probabilistic analysis to determine the incremental cost of multi-gene pharmacogenomic testing versus treatment as usual per quality-adjusted life-year (QALY) gained for people with major depression who had inadequate response to one or more antidepressant medications. In the reference case (with GeneSight-guided care), we considered a 1-year time horizon with an Ontario Ministry of Health perspective. We also estimated the 5-year budget impact of publicly funding multi-gene pharmacogenomic testing for people with major depression in Ontario.To contextualize the potential value of multi-gene pharmacogenomic testing that includes decision-support tools, we spoke with people who have major depression and their families.</p><p><strong>Results: </strong>We included 14 studies in the clinical evidence review that evaluated six multi-gene pharmacogenomic tests. Although all tests included decision-support tools, they otherwise differed greatly, as did study design, populations included in studies, and outcomes reported. Little or no improvement was observed on change in HAM-D17 depression score compared with treatment as usual for any test evaluated (GRADE: Low-Very Low). GeneSight- and NeuroIDgenetix-guided medication selection led to statistically significant improvements in response (GRADE: Low-Very Low) and remission (GRADE: Low-Very Low), while treatment guided by CNSdose led to significant improvement in remission rates (GRADE: Low), but the study did not report on response. Results were inconsistent and uncertain for the impact of Neuropharmagen, and no significant improvement was observed for Genecept or another unspecified test for either response or remission (GRADE: Low-Very Low). Neuropharmagen may reduce adverse events and CNSDose may reduce intolerability to medication, while no difference was observed in adverse events with GeneSight, Genecept, or another unspecified test (GRADE: Moderate-Very Low). No studies reported data on suicide, treatment adherence, relapse, recovery, or recurrence of depression symptoms.Our review included four model-based economic studies and found that multi-gene pharmacogenomic testing was associated with greater effectiveness and cost savings than treatment as usual, over long-term (i.e., 3-,5-year and lifetime) time horizons. Since none of the included studies was fully applicable to the Ontario health care system, we conducted a primary economic evaluation.Our reference case analysis over the 1-year time horizon found that multi-gene pharmacogenomic testing (with GeneSight) was associated with additional QALYs (0.03, 95% credible interval [CrI]: 0.005; 0.072) and additional costs ($1,906, 95% Crl: $688; $3,360). An incremental cost-effectiveness ratio was $60,564 per QALY gained. The probability of the intervention being cost-effective (vs. treatment as usual) was 36.8% at a willingness-to-pay amount of $50,000 per QALY (i.e., moderately likely not to be cost-effective), rising to 70.7% at a willingness-to-pay amount of $100,000 per QALY (i.e., moderately likely to be cost-effective). Evidence informing economic modeling of the reference case with GeneSight and other multi-gene pharmacogenomic tests was of low to very low quality, implying considerable uncertainty or low confidence in the effectiveness estimates. The price of the test, efficacy of the intervention on remission, time horizon, and analytic perspective were major determinants of the cost-effectiveness results. If the test price were assumed to be $2,162 (compared with $2,500 in the reference case), the intervention would be cost-effective at a willingness-to-pay amount of $50,000 per QALY; moreover, if the price decreased to $595, the intervention would be cost saving (or dominant) compared with treatment as usual.At an increasing uptake of 1% per year and a test price of $2,500, the annual budget impact of publicly funding multi-gene pharmacogenomic testing in Ontario over the next 5 years ranged from an additional $3.5 million in year 1 (at uptake of 1%) to $16.8 million in year 5. The 5-year budget impact was estimated at about $52 million.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side effects and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.</p><p><strong>Conclusions: </strong>Multi-gene pharmacogenomic testing that includes decision-support tools to guide medication selection for depression varies widely. Differences between individual tests must be considered, as clinical utility observed with one test might not apply to other tests. Overall, effectiveness was inconsistent among the six multi-gene pharmacogenomic tests we identified. Multi-gene pharmacogenomic tests may result in little or no difference in improvement in depression scores compared with treatment as usual, but some tests may improve response to treatment or remission from depression. The impact on adverse events is uncertain. The evidence, however, is uncertain, and therefore our confidence that these observed effects reflect the true effects is low to very low.For the management of major depression in people who had inadequate response to at least one medication, some multi-gene pharmacogenomic tests that include decision support tools are associated with additional costs and QALYs over the 1-year time horizon, and maybe be cost-effective at the willingness-to-pay amount of $100,000 per QALY. Publicly funding multi-gene pharmacogenomic testing in Ontario would result in additional annual costs of between $3.5 million and $16.8 million, with a total budget impact of about $52 million over the next 5 years.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side and help inform their medication choices. 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引用次数: 0
摘要
背景:重度抑郁症是一个重大的公共卫生问题,可影响人际关系,降低人们上学或工作的能力,并导致社会孤立。包括决策支持工具在内的多基因药物基因组学测试可以帮助预测哪种抑郁症药物和剂量最有可能导致对治疗的强烈反应,或者根据人们的基因有最低的不良事件风险。我们对多基因药物基因组学测试进行了健康技术评估,其中包括对重度抑郁症患者的决策支持工具。我们的评估评估了有效性、安全性、成本效益、公共资助多基因药物基因组学测试的预算影响以及患者的偏好和价值。方法:对临床证据进行系统的文献检索。我们使用Cochrane偏倚风险评估工具和非随机研究偏倚风险评估工具(RoBANS)评估每个纳入研究的偏倚风险,并根据建议评估、发展和评价分级(GRADE)工作组标准评估证据体的质量。我们对经济证据进行了系统的文献检索,以回顾已发表的多基因药物基因组学测试的成本效益研究,其中包括对重度抑郁症患者的决策支持工具。我们开发了一种状态转换模型,并进行了概率分析,以确定对一种或多种抗抑郁药物反应不足的重度抑郁症患者每质量调整生命年(QALY)获得的多基因药物基因组学检测与常规治疗的增量成本。在参考案例中(采用genesight指导的护理),我们从安大略省卫生部的角度考虑了1年的时间范围。我们还估计了安大略省对重度抑郁症患者进行多基因药物基因组学测试的5年预算影响。为了了解包括决策支持工具在内的多基因药物基因组测试的潜在价值,我们与患有严重抑郁症的人及其家人进行了交谈。结果:我们在临床证据综述中纳入了14项研究,评估了6项多基因药物基因组学测试。尽管所有测试都包括决策支持工具,但它们在其他方面存在很大差异,研究设计、研究人群和报告的结果也存在很大差异。与常规治疗相比,在任何评估的测试中,HAM-D17抑郁评分的变化几乎没有改善(GRADE: Low- very Low)。GeneSight和neuroidgenetix指导下的药物选择导致反应(GRADE: Low- very Low)和缓解(GRADE: Low- very Low)的统计学显著改善,而CNSdose指导下的治疗导致缓解率(GRADE: Low)的显着改善,但研究未报告反应。对于Neuropharmagen的影响,结果是不一致和不确定的,Genecept或另一个未指定的反应或缓解试验没有观察到显著的改善(GRADE: Low- very Low)。Neuropharmagen可以减少不良事件,CNSDose可以减少对药物的不耐受性,而不良事件与GeneSight、Genecept或另一个未指定的试验(GRADE:中度-极低)没有差异。没有研究报告自杀、治疗依从性、复发、恢复或抑郁症状复发的数据。我们的综述包括四项基于模型的经济研究,发现在长期(即3年、5年和终身)时间范围内,多基因药物基因组学检测与常规治疗相比具有更高的有效性和成本节约。由于纳入的研究没有一项完全适用于安大略省的卫生保健系统,我们进行了初步的经济评估。我们对1年时间跨度的参考病例分析发现,多基因药物基因组学检测(使用GeneSight)与额外的qaly相关(0.03,95%可信区间[CrI]: 0.005;0.072美元)和额外费用(1,906美元,95% Crl: 688美元;3360美元)。增加的成本效益比为每增加一个质量质量为60 564美元。当每次QALY愿意支付金额为50,000美元(即,中等可能不具有成本效益)时,干预措施具有成本效益的概率为36.8%,而当每次QALY愿意支付金额为100,000美元(即,中等可能具有成本效益)时,干预措施的成本效益概率上升至70.7%。使用GeneSight和其他多基因药物基因组学测试对参考病例进行经济建模的证据质量很低或非常低,这意味着在有效性估计中存在相当大的不确定性或低置信度。测试的价格、干预的缓解效果、时间范围和分析角度是成本-效果结果的主要决定因素。 如果假设测试价格为2162美元(与参考案例中的2500美元相比),干预措施将具有成本效益,每个QALY的支付意愿为50,000美元;此外,如果价格降至595美元,与常规治疗相比,干预将节省成本(或占主导地位)。以每年1%的增长速度和2500美元的测试价格,安大略省未来5年公共资助多基因药物基因组学测试的年度预算影响范围从第一年的350万美元(以1%的增长速度)到第五年的1680万美元不等。5年预算影响估计约为5 200万美元。重度抑郁症患者和护理人员普遍支持多基因药物基因组学测试,因为他们相信这可以提供符合他们价值观的指导。他们希望这样的指导能加速症状缓解,减少副作用,并帮助他们选择药物。一些患者表达了对检测结果保密的担忧,以及医生可能会牺牲以患者为中心的护理来遵循药物基因组学指导。结论:包括决策支持工具在内的多基因药物基因组学检测在指导抑郁症药物选择方面存在很大差异。必须考虑个别试验之间的差异,因为用一种试验观察到的临床效用可能不适用于其他试验。总的来说,我们确定的六种多基因药物基因组学测试的有效性是不一致的。与常规治疗相比,多基因药物基因组学测试在改善抑郁症评分方面可能几乎没有差异,但有些测试可能改善对治疗的反应或抑郁症的缓解。对不良事件的影响尚不确定。然而,证据是不确定的,因此我们对这些观察到的效果反映真实效果的信心很低,甚至很低。对于对至少一种药物反应不足的重度抑郁症患者的管理,一些包括决策支持工具的多基因药物基因组学测试与1年时间范围内的额外费用和QALY相关,并且在每个QALY的愿意支付金额为100,000美元时可能具有成本效益。公开资助安大略省的多基因药物基因组学测试将导致每年额外的成本在350万至1680万美元之间,未来5年的预算影响总额约为5200万美元。重度抑郁症患者和护理人员普遍支持多基因药物基因组学测试,因为他们相信这可以提供符合他们价值观的指导。他们希望这样的指导能加速症状缓解,减少副作用,并帮助他们选择药物。一些患者表达了对检测结果保密的担忧,以及医生可能会牺牲以患者为中心的护理来遵循药物基因组学指导。
Multi-gene Pharmacogenomic Testing That Includes Decision-Support Tools to Guide Medication Selection for Major Depression: A Health Technology Assessment.
Background: Major depression is a substantial public health concern that can affect personal relationships, reduce people's ability to go to school or work, and lead to social isolation. Multi-gene pharmacogenomic testing that includes decision-support tools can help predict which depression medications and dosages are most likely to result in a strong response to treatment or to have the lowest risk of adverse events on the basis of people's genes.We conducted a health technology assessment of multi-gene pharmacogenomic testing that includes decision-support tools for people with major depression. Our assessment evaluated effectiveness, safety, cost-effectiveness, the budget impact of publicly funding multi-gene pharmacogenomic testing, and patient preferences and values.
Methods: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane Risk of Bias Tool and the Risk of Bias Assessment Tool for Nonrandomized studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria.We performed a systematic literature search of the economic evidence to review published cost-effectiveness studies on multi-gene pharmacogenomic testing that includes a decision-support tool in people with major depression. We developed a state-transition model and conducted a probabilistic analysis to determine the incremental cost of multi-gene pharmacogenomic testing versus treatment as usual per quality-adjusted life-year (QALY) gained for people with major depression who had inadequate response to one or more antidepressant medications. In the reference case (with GeneSight-guided care), we considered a 1-year time horizon with an Ontario Ministry of Health perspective. We also estimated the 5-year budget impact of publicly funding multi-gene pharmacogenomic testing for people with major depression in Ontario.To contextualize the potential value of multi-gene pharmacogenomic testing that includes decision-support tools, we spoke with people who have major depression and their families.
Results: We included 14 studies in the clinical evidence review that evaluated six multi-gene pharmacogenomic tests. Although all tests included decision-support tools, they otherwise differed greatly, as did study design, populations included in studies, and outcomes reported. Little or no improvement was observed on change in HAM-D17 depression score compared with treatment as usual for any test evaluated (GRADE: Low-Very Low). GeneSight- and NeuroIDgenetix-guided medication selection led to statistically significant improvements in response (GRADE: Low-Very Low) and remission (GRADE: Low-Very Low), while treatment guided by CNSdose led to significant improvement in remission rates (GRADE: Low), but the study did not report on response. Results were inconsistent and uncertain for the impact of Neuropharmagen, and no significant improvement was observed for Genecept or another unspecified test for either response or remission (GRADE: Low-Very Low). Neuropharmagen may reduce adverse events and CNSDose may reduce intolerability to medication, while no difference was observed in adverse events with GeneSight, Genecept, or another unspecified test (GRADE: Moderate-Very Low). No studies reported data on suicide, treatment adherence, relapse, recovery, or recurrence of depression symptoms.Our review included four model-based economic studies and found that multi-gene pharmacogenomic testing was associated with greater effectiveness and cost savings than treatment as usual, over long-term (i.e., 3-,5-year and lifetime) time horizons. Since none of the included studies was fully applicable to the Ontario health care system, we conducted a primary economic evaluation.Our reference case analysis over the 1-year time horizon found that multi-gene pharmacogenomic testing (with GeneSight) was associated with additional QALYs (0.03, 95% credible interval [CrI]: 0.005; 0.072) and additional costs ($1,906, 95% Crl: $688; $3,360). An incremental cost-effectiveness ratio was $60,564 per QALY gained. The probability of the intervention being cost-effective (vs. treatment as usual) was 36.8% at a willingness-to-pay amount of $50,000 per QALY (i.e., moderately likely not to be cost-effective), rising to 70.7% at a willingness-to-pay amount of $100,000 per QALY (i.e., moderately likely to be cost-effective). Evidence informing economic modeling of the reference case with GeneSight and other multi-gene pharmacogenomic tests was of low to very low quality, implying considerable uncertainty or low confidence in the effectiveness estimates. The price of the test, efficacy of the intervention on remission, time horizon, and analytic perspective were major determinants of the cost-effectiveness results. If the test price were assumed to be $2,162 (compared with $2,500 in the reference case), the intervention would be cost-effective at a willingness-to-pay amount of $50,000 per QALY; moreover, if the price decreased to $595, the intervention would be cost saving (or dominant) compared with treatment as usual.At an increasing uptake of 1% per year and a test price of $2,500, the annual budget impact of publicly funding multi-gene pharmacogenomic testing in Ontario over the next 5 years ranged from an additional $3.5 million in year 1 (at uptake of 1%) to $16.8 million in year 5. The 5-year budget impact was estimated at about $52 million.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side effects and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.
Conclusions: Multi-gene pharmacogenomic testing that includes decision-support tools to guide medication selection for depression varies widely. Differences between individual tests must be considered, as clinical utility observed with one test might not apply to other tests. Overall, effectiveness was inconsistent among the six multi-gene pharmacogenomic tests we identified. Multi-gene pharmacogenomic tests may result in little or no difference in improvement in depression scores compared with treatment as usual, but some tests may improve response to treatment or remission from depression. The impact on adverse events is uncertain. The evidence, however, is uncertain, and therefore our confidence that these observed effects reflect the true effects is low to very low.For the management of major depression in people who had inadequate response to at least one medication, some multi-gene pharmacogenomic tests that include decision support tools are associated with additional costs and QALYs over the 1-year time horizon, and maybe be cost-effective at the willingness-to-pay amount of $100,000 per QALY. Publicly funding multi-gene pharmacogenomic testing in Ontario would result in additional annual costs of between $3.5 million and $16.8 million, with a total budget impact of about $52 million over the next 5 years.People with major depression and caregivers generally supported multi-gene pharmacogenomic testing because they believed it could provide guidance that fit their values. They hoped such guidance would speed symptom relief, would reduce side and help inform their medication choices. Some patients expressed concerns over maintaining confidentiality of test results and the possibility that physicians would sacrifice patient-centred care to follow pharmacogenomic guidance.