Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial
常规癌症治疗期间基于患者报告结果的症状监测：一项随机对照试验
Authors Info & Affiliations
作者：Ethan Basch ebasch@med.unc.edu, Allison M. Deal, Mark G. Kris, Howard I. Scher, Clifford A. Hudis, Paul Sabbatini, Lauren Rogak, … 显示全部 …, 以及 Deborah Schrag 作者信息与所属机构
作者：Ethan Basch ebasch@med.unc.edu, Allison M. Deal, Mark G. Kris, Howard I. Scher, Clifford A. Hudis, Paul Sabbatini, Lauren Rogak, … 显示全部 …, 以及 Deborah Schrag 作者信息与所属机构
Publication: Journal of Clinical Oncology
发表期刊：临床肿瘤学杂志
发表期刊：临床肿瘤学杂志
Abstract 摘要
Purpose 目的
There is growing interest to enhance symptom monitoring during routine cancer care using patient-reported outcomes, but evidence of impact on clinical outcomes is limited.
在常规癌症护理中，越来越多的人对使用患者报告的结果来增强症状监测感兴趣，但临床结果影响的证据有限。
在常规癌症护理中，越来越多的人对使用患者报告的结果来增强症状监测感兴趣，但临床结果影响的证据有限。
Methods 方法
We randomly assigned patients receiving routine outpatient chemotherapy for advanced solid tumors at Memorial Sloan Kettering Cancer Center to report 12 common symptoms via tablet computers or to receive usual care consisting of symptom monitoring at the discretion of clinicians. Those with home computers received weekly e-mail prompts to report between visits. Treating physicians received symptom printouts at visits, and nurses received e-mail alerts when participants reported severe or worsening symptoms. The primary outcome was change in health-related quality of life (HRQL) at 6 months compared with baseline, measured by the EuroQol EQ-5D Index. Secondary endpoints included emergency room (ER) visits, hospitalizations, and survival.
我们将在纪念斯隆-凯特琳癌症中心接受常规门诊化疗的晚期实体瘤患者随机分配，通过平板电脑报告 12 种常见症状，或接受由临床医生自行决定的症状监测的常规护理。拥有家用电脑的患者每周会收到电子邮件提示，在就诊间期进行报告。主治医生在就诊时收到症状打印件，当参与者报告严重或恶化的症状时，护士会收到电子邮件警报。主要结局是与基线相比，6 个月时健康相关生活质量（HRQL）的变化，通过 EuroQol EQ-5D 指数测量。次要终点包括急诊室（ER）就诊、住院和生存情况。
我们将在纪念斯隆-凯特琳癌症中心接受常规门诊化疗的晚期实体瘤患者随机分配，通过平板电脑报告 12 种常见症状，或接受由临床医生自行决定的症状监测的常规护理。拥有家用电脑的患者每周会收到电子邮件提示，在就诊间期进行报告。主治医生在就诊时收到症状打印件，当参与者报告严重或恶化的症状时，护士会收到电子邮件警报。主要结局是与基线相比，6 个月时健康相关生活质量（HRQL）的变化，通过 EuroQol EQ-5D 指数测量。次要终点包括急诊室（ER）就诊、住院和生存情况。
Results 结果
Among 766 patients allocated, HRQL improved among more participants in the intervention group than usual care (34% v 18%) and worsened among fewer (38% v 53%; P < .001). Overall, mean HRQL declined by less in the intervention group than usual care (1.4- v 7.1-point drop; P < .001). Patients receiving intervention were less frequently admitted to the ER (34% v 41%; P = .02) or hospitalized (45% v 49%; P = .08) and remained on chemotherapy longer (mean, 8.2 v 6.3 months; P = .002). Although 75% of the intervention group was alive at 1 year, 69% with usual care survived the year (P = .05), with differences also seen in quality-adjusted survival (mean of 8.7 v. 8.0 months; P = .004). Benefits were greater for participants lacking prior computer experience. Most patients receiving intervention (63%) reported severe symptoms during the study. Nurses frequently initiated clinical actions in response to e-mail alerts.
在分配的 766 名患者中，干预组的生活质量（HRQL）改善的参与者比例高于常规护理组（34% vs 18%），且恶化的比例更低（38% vs 53%；P < .001）。总体而言，干预组的生活质量平均下降幅度小于常规护理组（1.4 分 vs 7.1 分下降；P < .001）。接受干预的患者急诊就诊（34% vs 41%；P = .02）或住院（45% vs 49%；P = .08）的频率较低，且化疗持续时间更长（平均 8.2 个月 vs 6.3 个月；P = .002）。尽管干预组中 75%的患者在 1 年后仍存活，而常规护理组中 69%的患者存活（P = .05），但质量调整后的生存时间也存在差异（平均 8.7 个月 vs 8.0 个月；P = .004）。对于缺乏计算机使用经验的参与者，获益更大。大多数接受干预的患者（63%）在研究期间报告了严重症状。护士经常根据电子邮件警报启动临床行动。
在分配的 766 名患者中，干预组的生活质量（HRQL）改善的参与者比例高于常规护理组（34% vs 18%），且恶化的比例更低（38% vs 53%；P < .001）。总体而言，干预组的生活质量平均下降幅度小于常规护理组（1.4 分 vs 7.1 分下降；P < .001）。接受干预的患者急诊就诊（34% vs 41%；P = .02）或住院（45% vs 49%；P = .08）的频率较低，且化疗持续时间更长（平均 8.2 个月 vs 6.3 个月；P = .002）。尽管干预组中 75%的患者在 1 年后仍存活，而常规护理组中 69%的患者存活（P = .05），但质量调整后的生存时间也存在差异（平均 8.7 个月 vs 8.0 个月；P = .004）。对于缺乏计算机使用经验的参与者，获益更大。大多数接受干预的患者（63%）在研究期间报告了严重症状。护士经常根据电子邮件警报启动临床行动。
Conclusion 结论
Clinical benefits were associated with symptom self-reporting during cancer care.
临床获益与癌症治疗期间的症状自我报告相关。
临床获益与癌症治疗期间的症状自我报告相关。
Accompanying Articles 相关文章
Introduction 简介
Symptoms are common among patients receiving treatment of advanced cancers1,2 and often go undetected.3-6 Systematic collection of symptom information using patient-reported outcome (PRO) standardized questionnaires has been suggested as an approach to improve symptom control.7,8 Several web-based systems exist9,10 and have been shown to prompt clinicians to intensify symptom management,11-13 to improve symptom control,11,13-15 and to enhance patient-clinician communication, patient satisfaction, and well-being.16-22 Most patients are willing and able to self-report via the web, even close to the end of life.23
接受晚期癌症治疗的病人中，症状普遍存在 1,2 且常被忽视。 3-6 使用患者报告结局（PRO）标准化问卷系统收集症状信息已被建议作为改善症状控制的方法。 7,8 存在多种基于网络的系统 9,10 ，这些系统已被证明能促使临床医生加强症状管理， 11-13 改善症状控制， 11,13-15 并增强患者与临床医生的沟通、患者满意度及福祉。 16-22 大多数患者愿意且能够通过网络进行自我报告，即使在生命末期附近。 23
接受晚期癌症治疗的病人中，症状普遍存在 1,2 且常被忽视。 3-6 使用患者报告结局（PRO）标准化问卷系统收集症状信息已被建议作为改善症状控制的方法。 7,8 存在多种基于网络的系统 9,10 ，这些系统已被证明能促使临床医生加强症状管理， 11-13 改善症状控制， 11,13-15 并增强患者与临床医生的沟通、患者满意度及福祉。 16-22 大多数患者愿意且能够通过网络进行自我报告，即使在生命末期附近。 23
The effects of symptom self-reporting on clinical outcomes are not established, leaving open the question of whether the benefits of systems to elicit PRO self-reports outweigh their added cost and burden.9,16,17 Symptoms precipitate emergency room (ER) visits and hospital admissions,24 but it is not known if such visits are potentially avoidable through improved prospective monitoring. Several symptoms are associated with worse survival in advanced cancer and lead to functional impairment and deconditioning.25 Therefore, improved symptom control may improve survival. To address these questions, we conducted a single-center randomized controlled trial to test whether systematic web-based collection of patient-reported symptoms during chemotherapy treatment, with automated alerts to clinicians for severe or worsening symptoms, improves health-related quality of life (HRQL) as well as survival, quality-adjusted survival, ER use, and hospitalization.
症状自我报告对临床结果的影响尚未明确，因此系统收集患者报告结果（PRO）的益处是否超过其增加的成本和负担仍是一个悬而未决的问题。 9,16,17 症状会引发急诊室（ER）就诊和住院， 24 但尚不清楚通过改进的前瞻性监测是否可以避免此类就诊。多种症状与晚期癌症患者的生存率下降相关，并导致功能障碍和体能下降。 25 因此，改善症状控制可能提高生存率。为解答这些问题，我们开展了一项单中心随机对照试验，以测试在化疗治疗期间，通过系统化的网络平台收集患者报告的症状，并自动向临床医生发出严重或恶化症状的警报，是否能改善与健康相关的生命质量（HRQL）以及生存率、质量调整生存率、急诊室使用率和住院率。
症状自我报告对临床结果的影响尚未明确，因此系统收集患者报告结果（PRO）的益处是否超过其增加的成本和负担仍是一个悬而未决的问题。 9,16,17 症状会引发急诊室（ER）就诊和住院， 24 但尚不清楚通过改进的前瞻性监测是否可以避免此类就诊。多种症状与晚期癌症患者的生存率下降相关，并导致功能障碍和体能下降。 25 因此，改善症状控制可能提高生存率。为解答这些问题，我们开展了一项单中心随机对照试验，以测试在化疗治疗期间，通过系统化的网络平台收集患者报告的症状，并自动向临床医生发出严重或恶化症状的警报，是否能改善与健康相关的生命质量（HRQL）以及生存率、质量调整生存率、急诊室使用率和住院率。
Methods 方法
Trial Design and Participants
试验设计和参与者
Patients initiating chemotherapy at Memorial Sloan Kettering Cancer Center (MSK) in New York for metastatic breast, genitourinary, gynecologic, or lung cancers were enrolled in a nonblinded, randomized, controlled trial of web-based self-reporting of symptoms, compared with usual care. The study protocol was approved by the MSK institutional review board and registered on ClinicalTrials.gov (NCT00578006).
在纽约纪念斯隆-凯特琳癌症中心（MSK）开始接受化疗的转移性乳腺癌、泌尿生殖系统癌、妇科癌或肺癌患者被纳入一项非盲、随机、对照试验，比较基于网络的症状自我报告与常规护理。该研究方案已获得 MSK 机构审查委员会的批准，并在 ClinicalTrials.gov 上注册（NCT00578006）。
在纽约纪念斯隆-凯特琳癌症中心（MSK）开始接受化疗的转移性乳腺癌、泌尿生殖系统癌、妇科癌或肺癌患者被纳入一项非盲、随机、对照试验，比较基于网络的症状自我报告与常规护理。该研究方案已获得 MSK 机构审查委员会的批准，并在 ClinicalTrials.gov 上注册（NCT00578006）。
Patients were eligible if they planned to receive chemotherapy at MSK and could read English. Patients were ineligible if they were participating in an investigational treatment, because such studies stipulate structured symptom reporting. The included tumor types were selected because they represent a spectrum of symptoms related to cancer and treatment; metastatic disease was specified because treatment is often continuous and symptoms are common.1 All participants provided written informed consent. Randomization was conducted by the institutional Biostatics Service via a computer system using randomly permutated blocks. Participants remained on study until discontinuation of cancer treatment, voluntary withdrawal, or death.
患者如果计划在 MSK 接受化疗且能阅读英语，则符合资格。如果患者正在参与一项研究性治疗，则不符合资格，因为此类研究规定了结构化的症状报告。所纳入的肿瘤类型因其代表了与癌症和治疗相关的症状谱系而被选中；指定了转移性疾病，因为治疗通常是持续的，且症状常见。 1 所有参与者均提供了书面知情同意书。随机化由机构生物统计服务部门通过使用随机排列块的计算机系统进行。参与者在癌症治疗停止、自愿退出或死亡之前一直参与研究。
患者如果计划在 MSK 接受化疗且能阅读英语，则符合资格。如果患者正在参与一项研究性治疗，则不符合资格，因为此类研究规定了结构化的症状报告。所纳入的肿瘤类型因其代表了与癌症和治疗相关的症状谱系而被选中；指定了转移性疾病，因为治疗通常是持续的，且症状常见。 1 所有参与者均提供了书面知情同意书。随机化由机构生物统计服务部门通过使用随机排列块的计算机系统进行。参与者在癌症治疗停止、自愿退出或死亡之前一直参与研究。
Preplanned Subgroups 预先规划的子组
Before randomization, participants were assigned to one of two subgroups based on level of prior computer and e-mail use. Those with regular access to a computer and e-mail use at least weekly were assigned to a computer-experienced subgroup; the remainder were assigned to a computer-inexperienced subgroup. This approach was based on evidence that patients with computer experience are more receptive to electronic self-reporting than those with less computer experience.26 The patients in each subgroup were independently allocated to self-reporting versus usual care (1:1 in the computer-experienced subgroup and enriched at 2:1 in the computer-inexperienced subgroup, to enable an assessment of the logistics of obtaining PROs in this group as a part of a parallel feasibility study).
随机化前，根据参与者先前的计算机和电子邮件使用水平，将其分配到两个子组之一。那些定期使用计算机并至少每周使用电子邮件的人被分配到计算机经验丰富的子组；其余人则被分配到计算机经验不足的子组。这种方法基于以下证据：与计算机经验较少的人相比，有计算机经验的病人更愿意接受电子自我报告。 26 每个子组的病人独立地被分配到自我报告与常规护理（计算机经验丰富的子组为 1:1，计算机经验不足的子组为 2:1，以评估在该组中获取患者报告结果（PROs）的物流情况，作为平行可行性研究的一部分）。
随机化前，根据参与者先前的计算机和电子邮件使用水平，将其分配到两个子组之一。那些定期使用计算机并至少每周使用电子邮件的人被分配到计算机经验丰富的子组；其余人则被分配到计算机经验不足的子组。这种方法基于以下证据：与计算机经验较少的人相比，有计算机经验的病人更愿意接受电子自我报告。 26 每个子组的病人独立地被分配到自我报告与常规护理（计算机经验丰富的子组为 1:1，计算机经验不足的子组为 2:1，以评估在该组中获取患者报告结果（PROs）的物流情况，作为平行可行性研究的一部分）。
Intervention 干预
Self-reporting was conducted via STAR (Symptom Tracking and Reporting), a web-based interface previously established as easy to use for patients with cancer with high symptom burdens.20,27-29 STAR includes questions adapted for patient use from the National Cancer Institute’s Common Terminology Criteria for Adverse Events,26,27 pertaining to 12 common symptoms experienced during chemotherapy1,30: appetite loss, constipation, cough, diarrhea, dyspnea, dysuria, fatigue, hot flashes, nausea, pain, neuropathy, and vomiting. These symptoms are graded on a five-point scale from 0 (not present) to 4 (disabling) based on clinical criteria.31 STAR did not allow skipped questions or free-text responses.
自我报告通过 STAR（症状追踪与报告）进行，这是一个先前已建立的基于网络的界面，便于高症状负担的癌症患者使用。 20,27-29 STAR 包含从美国国家癌症研究所的常见不良事件术语标准中改编的适用于患者的问题， 26,27 涉及化疗期间常见的 12 种症状 1,30 ：食欲丧失、便秘、咳嗽、腹泻、呼吸困难、排尿困难、疲劳、潮热、恶心、疼痛、神经病变和呕吐。这些症状根据临床标准在五点量表上分级，从 0（不存在）到 4（致残）。 31 STAR 不允许跳过问题或自由文本回答。
自我报告通过 STAR（症状追踪与报告）进行，这是一个先前已建立的基于网络的界面，便于高症状负担的癌症患者使用。 20,27-29 STAR 包含从美国国家癌症研究所的常见不良事件术语标准中改编的适用于患者的问题， 26,27 涉及化疗期间常见的 12 种症状 1,30 ：食欲丧失、便秘、咳嗽、腹泻、呼吸困难、排尿困难、疲劳、潮热、恶心、疼痛、神经病变和呕吐。这些症状根据临床标准在五点量表上分级，从 0（不存在）到 4（致残）。 31 STAR 不允许跳过问题或自由文本回答。
At enrollment, nonclinical study staff trained participants to use STAR and facilitated completion of a baseline self-report. At subsequent medical oncology or infusion suite visits, study staff invited participants to self-report either via wireless touchscreen tablet computers or freestanding computer kiosks. Participants in the computer-inexperienced subgroup were asked to self-report using STAR only at clinic visits. Participants in the computer-experienced subgroup were given remote access to STAR, with a weekly e-mail reminder encouraging but not requiring a between-visit report.
在登记时，非临床研究团队培训参与者使用 STAR，并协助完成基线自我报告。在随后的肿瘤内科或输液室就诊时，研究团队邀请参与者通过无线触摸屏平板电脑或独立计算机终端进行自我报告。计算机经验不足的子组参与者被要求仅在诊所就诊时使用 STAR 进行自我报告。计算机经验丰富的子组参与者获得了 STAR 的远程访问权限，并每周收到电子邮件提醒，鼓励但不强制要求在就诊间期进行报告。
在登记时，非临床研究团队培训参与者使用 STAR，并协助完成基线自我报告。在随后的肿瘤内科或输液室就诊时，研究团队邀请参与者通过无线触摸屏平板电脑或独立计算机终端进行自我报告。计算机经验不足的子组参与者被要求仅在诊所就诊时使用 STAR 进行自我报告。计算机经验丰富的子组参与者获得了 STAR 的远程访问权限，并每周收到电子邮件提醒，鼓励但不强制要求在就诊间期进行报告。
STAR triggered e-mail alerts to nurses whenever a patient-reported symptom worsened by ≥ 2 points or reached an absolute grade ≥ 3. The system informed participants that e-mails are not generally monitored after business hours, and participants were therefore encouraged to call the office at such times for symptoms of concern. A report tracking participants’ symptoms20,23,26 was printed at each clinic visit for both the nurse and treating oncologist. No specific guidance was provided to clinicians about what actions to take in response to alerts or printed symptom profiles.
每当患者报告的症状恶化≥2 分或达到绝对等级≥3 时，STAR 系统会触发向护士发送电子邮件警报。系统告知参与者，电子邮件通常不在工作时间之外监控，因此鼓励参与者在此时段内如有症状问题，请致电办公室。每次诊所就诊时，都会打印一份跟踪参与者症状的报告 20,23,26 ，供护士和主治肿瘤科医生参考。对于如何根据警报或打印的症状概况采取行动，临床医生未获得具体指导。
每当患者报告的症状恶化≥2 分或达到绝对等级≥3 时，STAR 系统会触发向护士发送电子邮件警报。系统告知参与者，电子邮件通常不在工作时间之外监控，因此鼓励参与者在此时段内如有症状问题，请致电办公室。每次诊所就诊时，都会打印一份跟踪参与者症状的报告 20,23,26 ，供护士和主治肿瘤科医生参考。对于如何根据警报或打印的症状概况采取行动，临床医生未获得具体指导。
Usual Care 常规护理
Usual care for both the computer-experienced and computer-inexperienced subgroups consisted of the standard procedure at MSK for monitoring and documenting symptoms, which is typical of medical oncology practice and was identical for both subgroups.5,20 Symptoms are discussed and documented in the medical record during clinical encounters between patients and their oncologists. Patients are encouraged to initiate telephone contact between visits for concerning symptoms.
计算机经验丰富和计算机经验不足两个子组的常规护理包括 MSK 的标准监测和症状记录程序，这是医学肿瘤学实践的典型做法，两个子组均相同。 5,20 在患者与其肿瘤科医生之间的临床会诊期间，症状会被讨论并记录在病历中。鼓励患者在就诊之间出现令人担忧的症状时主动电话联系。
计算机经验丰富和计算机经验不足两个子组的常规护理包括 MSK 的标准监测和症状记录程序，这是医学肿瘤学实践的典型做法，两个子组均相同。 5,20 在患者与其肿瘤科医生之间的临床会诊期间，症状会被讨论并记录在病历中。鼓励患者在就诊之间出现令人担忧的症状时主动电话联系。
Outcome Measures 结果指标
The primary outcome was change in HRQL at 6 months from baseline, measured via the EuroQol EQ-5D Index.32 The EQ-5D Index is a five-item questionnaire (measuring mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) that produces a composite score between 0 and 1 (multiplied by 100 to yield a result between 0-100) representing general health status, normalized for the US population.33,34 Lower scores represent worse HRQL. A score change of 6 points on the 0 to 100 scale is considered clinically meaningful in US cancer populations.35 The EQ-5D was administered via paper at clinic visits every 12 ± 4 weeks throughout study participation, with an understanding that in the routine care setting, clinic visit intervals vary between patients.
主要结果是基线后 6 个月时 HRQL 的变化，通过 EuroQol EQ-5D 指数进行测量。 32 EQ-5D 指数是一个五项问卷（测量活动能力、自我护理、日常活动、疼痛/不适以及焦虑/抑郁），生成一个介于 0 到 1 之间的综合得分（乘以 100 得到 0-100 之间的结果），代表一般健康状况，针对美国人群进行了标准化。 33,34 分数越低表示 HRQL 越差。在 0 到 100 的量表上，6 分的变化被认为在美国癌症人群中具有临床意义。 35 EQ-5D 通过纸质问卷在每次研究参与期间每 12 ± 4 周的诊所访问时进行管理，理解到在常规护理环境中，诊所访问间隔因患者而异。
主要结果是基线后 6 个月时 HRQL 的变化，通过 EuroQol EQ-5D 指数进行测量。 32 EQ-5D 指数是一个五项问卷（测量活动能力、自我护理、日常活动、疼痛/不适以及焦虑/抑郁），生成一个介于 0 到 1 之间的综合得分（乘以 100 得到 0-100 之间的结果），代表一般健康状况，针对美国人群进行了标准化。 33,34 分数越低表示 HRQL 越差。在 0 到 100 的量表上，6 分的变化被认为在美国癌症人群中具有临床意义。 35 EQ-5D 通过纸质问卷在每次研究参与期间每 12 ± 4 周的诊所访问时进行管理，理解到在常规护理环境中，诊所访问间隔因患者而异。
Survival at 1 year was tabulated based on medical records and Social Security Death Index data. Quality-adjusted survival was evaluated by multiplying EQ-5D scores by survival time for each patient.36 Time to first ER visit and time to first hospitalization at MSK were based on admissions data in the medical record. Time receiving active cancer treatment was abstracted from medical charts. The number of nursing calls to patients was tabulated based on nursing logs in the medical record.
1 年生存率根据医疗记录和社会安全死亡指数数据进行统计。质量调整生存期通过将每位患者的 EQ-5D 评分乘以其生存时间来评估。 36 首次急诊就诊时间和在 MSK 首次住院时间基于医疗记录中的入院数据。接受积极癌症治疗的时间从医疗图表中摘录。护理人员对患者的呼叫次数根据医疗记录中的护理日志进行统计。
1 年生存率根据医疗记录和社会安全死亡指数数据进行统计。质量调整生存期通过将每位患者的 EQ-5D 评分乘以其生存时间来评估。 36 首次急诊就诊时间和在 MSK 首次住院时间基于医疗记录中的入院数据。接受积极癌症治疗的时间从医疗图表中摘录。护理人员对患者的呼叫次数根据医疗记录中的护理日志进行统计。
Adherence with STAR self-reporting was assessed by calculating the proportion of participants completing questionnaires at each successive visit. For computer-inexperienced participants to be considered adherent at a given visit, a self-report must have been completed at the time of that visit. For computer-experienced participants to be adherent at a given visit, a STAR report had to be completed remotely within 72 hours. Nurses used a standardized form to record if and what clinical actions were taken in response to e-mail alerts.
通过计算每次随访中完成问卷的参与者比例，评估了与 STAR 自我报告的一致性。对于计算机经验不足的参与者，若要在某次随访中被视为遵守规定，必须在随访时完成自我报告。对于计算机经验丰富的参与者，若要在某次随访中遵守规定，必须在 72 小时内远程完成 STAR 报告。护士使用标准化表格记录是否以及采取了哪些临床行动以响应电子邮件警报。
通过计算每次随访中完成问卷的参与者比例，评估了与 STAR 自我报告的一致性。对于计算机经验不足的参与者，若要在某次随访中被视为遵守规定，必须在随访时完成自我报告。对于计算机经验丰富的参与者，若要在某次随访中遵守规定，必须在 72 小时内远程完成 STAR 报告。护士使用标准化表格记录是否以及采取了哪些临床行动以响应电子邮件警报。
Statistical Analysis 统计分析
The study was designed to accommodate combined and separate analyses of the computer-experienced and computer-inexperienced subgroups. Based on prior work,28 it was projected that 30% to 40% of participants would fall in the inexperienced category. The experienced subgroup was randomized 1:1 and the inexperienced was randomized 2:1, to facilitate focus on the feasibility of obtaining PROs in this group. The study planned to enroll until 225 patients were allocated within the smaller inexperienced subgroup (150 assigned to STAR and 75 to usual care). With 225 participants in the inexperienced subgroup, there was 80% power to detect an effect size of 0.40 in mean EQ-5D index change from baseline between arms using a t test with a two-sided α of 0.05.
该研究旨在适应对有计算机经验和无计算机经验子组的合并及单独分析。根据先前的工作， 28 预计 30%至 40%的参与者将属于无经验类别。有经验子组按 1:1 随机分配，而无经验子组按 2:1 随机分配，以便集中关注在该群体中获取患者报告结果（PROs）的可行性。研究计划招募直至 225 名患者分配到较小的无经验子组（150 名分配到 STAR，75 名分配到常规护理）。在无经验子组中有 225 名参与者的情况下，使用双侧α为 0.05 的 t 检验，有 80%的把握度检测各组间从基线到 EQ-5D 指数变化的均值差异为 0.40 的效果量。
该研究旨在适应对有计算机经验和无计算机经验子组的合并及单独分析。根据先前的工作， 28 预计 30%至 40%的参与者将属于无经验类别。有经验子组按 1:1 随机分配，而无经验子组按 2:1 随机分配，以便集中关注在该群体中获取患者报告结果（PROs）的可行性。研究计划招募直至 225 名患者分配到较小的无经验子组（150 名分配到 STAR，75 名分配到常规护理）。在无经验子组中有 225 名参与者的情况下，使用双侧α为 0.05 的 t 检验，有 80%的把握度检测各组间从基线到 EQ-5D 指数变化的均值差异为 0.40 的效果量。
For the primary quality-of-life analysis, EQ-5D index scores for participants in each study arm were calculated at 6 months and compared with baseline scores, excluding those who did not complete any postbaseline EQ-5D questionnaire and using the last postbaseline observation carried forward when available for patients without 6-month data. The proportion of patients in each arm who experienced improved, unchanged, or worsened scores from baseline was compared using Fisher’s exact test. This analysis was conducted both for any level of change from baseline and for a 6-point change from baseline, which is considered as clinically meaningful.34 Mean score changes from baseline were compared using two group t tests. A multivariable linear regression model, with change score as the dependent variable, adjusted for covariates including age, sex, cancer type, race, and education level. Multiple sensitivity imputation analyses were conducted including last observation carried forward but including baseline observations for patients with no postbaseline EQ-5D score, no observations carried forward, minimum observation values carried forward, average observation values carried forward, and last observation carried forward but assigning an EQ-5D value of zero if death occurred before 6 months. For each method, analyses were conducted separately for the whole group and for the subgroups based on computer experience.
对于主要的生活质量分析，计算了每个研究组参与者在 6 个月时的 EQ-5D 指数得分，并与基线得分进行比较，排除了未完成任何基线后 EQ-5D 问卷的参与者，并在有 6 个月数据缺失的患者中使用最后一次基线后观察结果进行填补。使用 Fisher 精确检验比较了每个组中从基线得分改善、不变或恶化的患者比例。此分析既针对基线得分的任何变化，也针对基线得分 6 分的变化，后者被认为具有临床意义。 34 使用两组 t 检验比较了基线得分的平均变化。建立了一个多变量线性回归模型，以变化得分为因变量，调整了包括年龄、性别、癌症类型、种族和教育水平在内的协变量。 进行了多项敏感性插补分析，包括使用最后一次观察值向前填充，但包含没有基线后 EQ-5D 分数的患者的基线观察值、无观察值向前填充、最小观察值向前填充、平均观察值向前填充，以及最后一次观察值向前填充但在 6 个月前死亡的情况下分配 EQ-5D 值为零。对于每种方法，分别对整个组和基于计算机经验的子组进行了分析。
对于主要的生活质量分析，计算了每个研究组参与者在 6 个月时的 EQ-5D 指数得分，并与基线得分进行比较，排除了未完成任何基线后 EQ-5D 问卷的参与者，并在有 6 个月数据缺失的患者中使用最后一次基线后观察结果进行填补。使用 Fisher 精确检验比较了每个组中从基线得分改善、不变或恶化的患者比例。此分析既针对基线得分的任何变化，也针对基线得分 6 分的变化，后者被认为具有临床意义。 34 使用两组 t 检验比较了基线得分的平均变化。建立了一个多变量线性回归模型，以变化得分为因变量，调整了包括年龄、性别、癌症类型、种族和教育水平在内的协变量。 进行了多项敏感性插补分析，包括使用最后一次观察值向前填充，但包含没有基线后 EQ-5D 分数的患者的基线观察值、无观察值向前填充、最小观察值向前填充、平均观察值向前填充，以及最后一次观察值向前填充但在 6 个月前死亡的情况下分配 EQ-5D 值为零。对于每种方法，分别对整个组和基于计算机经验的子组进行了分析。
For ER and hospitalization endpoints, cumulative incidence functions were calculated with death treated as a competing event.37 Competing risk regression was used to model risk with and without adjustment for baseline covariates.
对于急诊和住院终点，计算了将死亡视为竞争事件的累积发病率函数。 37 使用竞争风险回归模型，分别在调整和不调整基线协变量的情况下建模风险。
对于急诊和住院终点，计算了将死亡视为竞争事件的累积发病率函数。 37 使用竞争风险回归模型，分别在调整和不调整基线协变量的情况下建模风险。
Comparisons of the percentage of patients alive at 1 year were made using logistic regression, adjusting for baseline covariates, because complete survival data were available for all patients. For the quality-adjusted survival analysis, participants’ average EQ-5D scores were multiplied by survival times for each EQ-5D reporting interval during the initial year of enrollment; these values were summed to yield a total number of quality-adjusted life months for that patient during that year.35 Participants with missing baseline EQ-5D scores were excluded. Mean quality-adjusted life months were compared between arms in each cohort, using two group t tests. A multivariable linear regression model was used to adjust for the baseline covariates in Table 1.
使用逻辑回归对 1 年生存率百分比进行了比较，调整了基线协变量，因为所有患者的完整生存数据均可用。在质量调整生存分析中，参与者的平均 EQ-5D 评分乘以每个 EQ-5D 报告间隔的生存时间，这些值相加以得出该患者在该年内的质量调整生命月总数。 35 排除基线 EQ-5D 评分缺失的参与者。使用两组 t 检验比较各组间每个队列的平均质量调整生命月。采用多变量线性回归模型调整表 1 中的基线协变量。
使用逻辑回归对 1 年生存率百分比进行了比较，调整了基线协变量，因为所有患者的完整生存数据均可用。在质量调整生存分析中，参与者的平均 EQ-5D 评分乘以每个 EQ-5D 报告间隔的生存时间，这些值相加以得出该患者在该年内的质量调整生命月总数。 35 排除基线 EQ-5D 评分缺失的参与者。使用两组 t 检验比较各组间每个队列的平均质量调整生命月。采用多变量线性回归模型调整表 1 中的基线协变量。
| Characteristic 特征 | All Patients (N = 766) 所有患者（N = 766） | Computer-Experienced Subgroup (n = 539) 计算机经验子组（n = 539） | Computer-Inexperienced Subgroup (n = 227)* 计算机经验不足小组（n = 227）* | |||
|---|---|---|---|---|---|---|
| STAR (n = 441) STAR（n = 441） | Usual Care (n = 325) 常规护理 （n = 325） | STAR (n = 286) STAR（n = 286） | Usual Care (n = 253) 常规护理 （n = 253） | STAR (n = 155) STAR（n = 155） | Usual Care (n = 72) 常规护理 （n = 72） | |
| Age, median (range), years 年龄，中位数（范围），岁 | 61 (30-91) | 62 (26-88) | 59 (30-85) | 60 (26-88) | 67 (38-91) | 67 (44-86) |
| Female sex 女性性别 | 257 (58) | 187 (58) | 184 (64) | 152 (60) | 73 (47) | 35 (49) |
| Race 竞赛 | ||||||
| White 白 | 377 (86) | 283 (87) | 253 (89) | 230 (91) | 124 (80) | 53 (74) |
| Black† 黑† | 43 (10) | 24 (7) | 20 (7) | 10 (4) | 23 (15) | 14 (19) |
| Asian 亚洲 | 21 (5) | 18 (6) | 13 (5) | 13 (5) | 8 (5) | 5 (7) |
| Cancer type 癌症类型 | ||||||
| Genitourinary 泌尿生殖系统 | 143 (32) | 102 (31) | 78 (27) | 77 (30) | 65 (42) | 25 (35) |
| Gynecologic 妇科 | 97 (22) | 80 (25) | 67 (23) | 66 (26) | 30 (19) | 14 (19) |
| Breast 乳房 | 89 (20) | 54 (17) | 72 (25) | 47 (19) | 17 (11) | 7 (10) |
| Lung 肺 | 112 (25) | 89 (27) | 69 (24) | 63 (25) | 43 (28) | 26 (36) |
| Education 教育 | ||||||
| High school or less 高中或以下 | 106 (24) | 64 (20) | 46 (16) | 36 (14) | 60 (39) | 28 (39) |
| College 大学 | 205 (47) | 155 (48) | 143 (50) | 125 (49) | 62 (40) | 30 (42) |
| Graduate degree 研究生学位 | 130 (30) | 106 (33) | 97 (34) | 92 (36) | 33 (21) | 14 (19) |
| HRQL‡ | ||||||
| Mean 平均值 | 0.85 | 0.84 | 0.86 | 0.85 | 0.82 | 0.84 |
| Range 范围 | 0.27-1.0 | 0.20-1.00 | 0.33-1.00 | 0.22-1.00 | 0.27-1.00 | 0.20-1.00 |
| Days since initiation of chemotherapy 化疗开始后的天数 | ||||||
| Mean 平均值 | 46 | 40 | 44 | 41 | 51 | 39 |
| Range 范围 | 0-1,025 | 0-840 | 0-511 | 0-840 | 0-1,025 | 0-427 |
NOTE. Data presented as No. (%) unless otherwise noted. No significant differences between study arms were seen for any of the baseline characteristics in the study population overall or within either of the subgroups (all P > .3).
Abbreviations: HRQL, health related quality of life; STAR, Symptom Tracking and Reporting web-based self-reporting system (study intervention).
*
Randomized 2:1 in this subgroup.
†
Includes four patients categorized as “other” at enrollment and determined by chart review to have black race.
‡
HRQL measured via the EuroQoL EQ-5D questionnaire.
Two-sided P values of less than .05 were considered to indicate statistical significance.
双侧 P 值小于 0.05 被认为具有统计学意义。
双侧 P 值小于 0.05 被认为具有统计学意义。
Results 结果
Baseline Characteristics 基线特征
Between September 14, 2007 and January 6, 2011, 1,007 subjects were identified as potentially eligible and approached to participate. Of these, 154 were found to be ineligible, and 87 declined. The remaining 766 subjects were enrolled and randomly assigned, including 227 computer-inexperienced and 539 computer-experienced participants (Fig 1). Mean time on study was 7.4 months and median time was 3.7 months (range, 0.25 to 49), with a mean of 16 clinic visits per patient (range, 1 to 114).
2007 年 9 月 14 日至 2011 年 1 月 6 日期间，共识别出 1,007 名潜在符合条件的受试者并邀请参与。其中，154 名被判定为不符合条件，87 名拒绝参与。剩余的 766 名受试者被纳入并随机分配，包括 227 名计算机经验不足者和 539 名计算机经验丰富者（图 1）。平均研究时间为 7.4 个月，中位时间为 3.7 个月（范围为 0.25 至 49 个月），每位患者平均就诊 16 次（范围为 1 至 114 次）。
2007 年 9 月 14 日至 2011 年 1 月 6 日期间，共识别出 1,007 名潜在符合条件的受试者并邀请参与。其中，154 名被判定为不符合条件，87 名拒绝参与。剩余的 766 名受试者被纳入并随机分配，包括 227 名计算机经验不足者和 539 名计算机经验丰富者（图 1）。平均研究时间为 7.4 个月，中位时间为 3.7 个月（范围为 0.25 至 49 个月），每位患者平均就诊 16 次（范围为 1 至 114 次）。
图 1. CONSORT 流程图。*无计算机经验的患者按 2:1 比例分配，使用症状追踪与报告网络自报系统（STAR）与常规护理。 † 参与者在报告基线后生活质量（QOL）前退出研究。 ‡ 参与者在 6 个月前中止化疗治疗。 § 对在 6 个月前退出研究但报告了先前基线后 QOL 的参与者采用末次观测值结转（LOCF）。
Baseline characteristics were balanced between randomization arms in both the computer-experienced and -inexperienced subgroups (Table 1). Computer-inexperienced participants were significantly older, more often men, more often black, and less educated than computer-experienced participants (all P < .001).
基线特征在计算机经验组和无经验组中均在随机分配组间保持平衡（表 1）。无计算机经验的参与者显著年龄更大、男性更多、黑人更多、受教育程度较低，与有计算机经验的参与者相比（所有 P < .001）。
基线特征在计算机经验组和无经验组中均在随机分配组间保持平衡（表 1）。无计算机经验的参与者显著年龄更大、男性更多、黑人更多、受教育程度较低，与有计算机经验的参与者相比（所有 P < .001）。
Quality of Life 生活质量
HRQL scores improved by any amount from baseline to 6 months among more participants in the STAR arm than in the usual care arm (34% v 18%) and worsened among fewer (38% v 53%; P < .001; Fig 2; Data Supplement). Similarly, more participants in the STAR arm experienced an improvement in HRQL by the previously established clinically meaningful score change threshold of ≥ 6 points34 compared with usual care (21% v 11%), and fewer experienced a ≥ 6-point worsening (28% v 37%; P = .001). Mean HRQL scores declined by less in the intervention arm compared with usual care (1.4- v 7.1-point drop; P < .001; Table 2). Although effect sizes were the same in the two subgroups (0.38), results were statistically significant in the computer-experienced subgroup (P < .001) but did not reach statistical significance in the relatively smaller computer-inexperienced subgroup (P = .06). Notably, 230 patients (30% of participants) died or discontinued cancer treatment before completing a follow-up HRQL questionnaire. In a sensitivity analysis that included these individuals by carrying forward their baseline HRQL values, results were similar; results were also robust across multiple additional sensitivity analyses (Data Supplement). In an analysis of the EQ-5D’s subdomains, three were statistically significantly better with STAR compared with usual care at 6 months compared with baseline, including Mobility (P = .02), Self-Care (P = .01), and Anxiety/Depression (P = .01), but did not reach significance for Pain/Discomfort (P = .05) or Usual Activities (P = .09).
HRQL 评分在基线至 6 个月期间，STAR 组中更多参与者有所改善，而常规护理组中较少（34% vs 18%），恶化者也更少（38% vs 53%；P < .001；图 2；数据补充）。同样，STAR 组中更多参与者达到了先前确立的临床意义评分变化阈值≥6 分 34 ，相比常规护理组（21% vs 11%），且更少参与者出现≥6 分的恶化（28% vs 37%；P = .001）。干预组相比常规护理组，平均 HRQL 评分下降较少（1.4 分 vs 7.1 分下降；P < .001；表 2）。尽管两个亚组的效果大小相同（0.38），但计算机经验丰富的亚组结果具有统计学显著性（P < .001），而相对较小的计算机经验不足亚组未达到统计学显著性（P = .06）。值得注意的是，230 名患者（占参与者的 30%）在完成随访 HRQL 问卷前死亡或中断了癌症治疗。 在包含这些个体并沿用其基线 HRQL 值的敏感性分析中，结果相似；在多项额外的敏感性分析中，结果同样稳健（数据补充）。在 EQ-5D 子域的分析中，与常规护理相比，STAR 在 6 个月时相对于基线在三个子域上显著改善，包括行动能力（P = .02）、自我护理（P = .01）和焦虑/抑郁（P = .01），但在疼痛/不适（P = .05）或日常活动（P = .09）方面未达到显著性。
HRQL 评分在基线至 6 个月期间，STAR 组中更多参与者有所改善，而常规护理组中较少（34% vs 18%），恶化者也更少（38% vs 53%；P < .001；图 2；数据补充）。同样，STAR 组中更多参与者达到了先前确立的临床意义评分变化阈值≥6 分 34 ，相比常规护理组（21% vs 11%），且更少参与者出现≥6 分的恶化（28% vs 37%；P = .001）。干预组相比常规护理组，平均 HRQL 评分下降较少（1.4 分 vs 7.1 分下降；P < .001；表 2）。尽管两个亚组的效果大小相同（0.38），但计算机经验丰富的亚组结果具有统计学显著性（P < .001），而相对较小的计算机经验不足亚组未达到统计学显著性（P = .06）。值得注意的是，230 名患者（占参与者的 30%）在完成随访 HRQL 问卷前死亡或中断了癌症治疗。 在包含这些个体并沿用其基线 HRQL 值的敏感性分析中，结果相似；在多项额外的敏感性分析中，结果同样稳健（数据补充）。在 EQ-5D 子域的分析中，与常规护理相比，STAR 在 6 个月时相对于基线在三个子域上显著改善，包括行动能力（P = .02）、自我护理（P = .01）和焦虑/抑郁（P = .01），但在疼痛/不适（P = .05）或日常活动（P = .09）方面未达到显著性。
图 2. 6 个月时与基线相比，健康相关生活质量变化的病人比例。对于每个研究组的病人，统计了其 EuroQol EQ-5D 指数评分在 6 个月时与基线相比改善、保持不变或恶化的比例。使用 6 分或更多的变化阈值重复了此分析，该变化量在美国癌症人群中被认为具有临床意义。结果显示（A）所有参与者，以及分别显示（B）有计算机经验子组和（C）无计算机经验子组。分析仅包括具有可用基线和基线后 EQ-5D 评分的病人。P 值通过 Fisher 精确检验计算，基于比较的三种分类（改善、不变、恶化）比较研究组。STAR，症状追踪与报告网络自我报告系统（研究干预）。
| Patients 患者 | N* | STAR (n = 277) STAR（n = 277） | Usual Care (n = 180) 常规护理 （n = 180） | P (Univariable)† P（单变量）† | P (Multivariable)† P（多变量）† | Effect Size 效应量 |
|---|---|---|---|---|---|---|
| Evaluable patients* 可评估患者* | 457 | |||||
| EQ-5D at baseline 基线 EQ-5D | 86.2 (84.7 to 87.7) 86.2（84.7 至 87.7） | 86.6 (84.7 to 88.5) 86.6（84.7 至 88.5） | ||||
| EQ-5D at 6 months EQ-5D 6 个月评估 | 84.8 (83.2 to 86.4) 84.8（83.2 至 86.4） | 79.5 (76.7 to 82.2) 79.5（76.7 至 82.2） | ||||
| Point drop from baseline | 1.4 (0.4 to 3.1) | 7.1 (4.8 to 9.5) | ||||
| Difference in point drop between arms | 5.7 | <.001 | <.001 | 0.37 | ||
| Subgroup analysis | ||||||
| Computer-inexperienced subgroup* | 116 | |||||
| EQ-5D at baseline | 83.6 (80.2 to 86.9) | 86.9 (81.9 to 91.9) | ||||
| EQ-5D at 6 months | 81.8 (78.2 to 85.3) | 78.6 (71.2 to 86.0) | ||||
| Point drop from baseline | 1.8 ( to 2.1 to 5.7) | 8.3 (3.6 to 13.1) | ||||
| Difference in point drop between arms | 6.5 | .06 | .11 | 0.38 | ||
| Computer-experienced subgroup* | 341 | |||||
| EQ-5D at baseline | 87.3 (85.7 to 88.6) | 86.5 (84.5 to 88.6) | ||||
| EQ-5D at 6 months | 86.1 (84.3 to 87.8) | 79.7 (76.7 to 82.7) | ||||
| Point drop from baseline | 1.2 (0.7 to 3.1) | 6.9 (4.2 to 9.5) | ||||
| Difference in point drop between arms | 5.7 | <.001 | <.001 | 0.38 | ||
NOTE. Data presented as mean (95% CI) unless otherwise noted.
Abbreviations: STAR, Symptom Tracking and Reporting web-based self-reporting system; EQ-5D, EuroQoL EQ-5D quality of life questionnaire.
*
Patents without postbaseline EQ-5D scores were not included in the primary health-related quality of life analysis but were included in the sensitivity analysis with similar results.
†
P values for between-arm comparisons. Multivariable analyses controlled for age, sex, cancer type, race, and education level. For overall analyses, subgroup assignment (computer experienced or computer inexperienced) was also included as a covariate.
ER Visits, Hospitalization, Cancer Treatment
急诊就诊、住院、癌症治疗
Fewer participants in the STAR arm visited the ER compared with usual care (34% v 41% at 1 year; P = .02; Fig 3). These differences appeared more pronounced in the computer-inexperienced subgroup (34% v 56%; P = .02) than in the computer-experienced subgroup (34% v 36%; P = .16). A similar trend was seen in the proportion of patients hospitalized at 1 year for the overall study population (45% v 49%; P = .08), again more pronounced and significant in the computer-inexperienced subgroup (44% v 63%; P = .003) but not in the computer-experienced subgroup (46% v 45%; P = .75; Data Supplement). Patients in the STAR arm received active chemotherapy treatment for significantly longer than usual care during the study, with a mean of 8.2 months (range, 0 to 49 months) versus 6.3 months (range, 0 to 41 months), respectively (P = .002), and a median of 4.1 months versus 3.5 months, respectively (P = .002).
与常规护理相比，参与 STAR 组的急诊就诊率较低（1 年时为 34% vs 41%；P = .02；图 3）。这些差异在计算机经验不足的亚组中更为明显（34% vs 56%；P = .02），而在计算机经验丰富的亚组中则不明显（34% vs 36%；P = .16）。总体研究人群中，1 年内住院患者比例也呈现类似趋势（45% vs 49%；P = .08），计算机经验不足的亚组中差异更为显著且具有统计学意义（44% vs 63%；P = .003），而在计算机经验丰富的亚组中则无显著差异（46% vs 45%；P = .75；数据补充）。STAR 组患者在研究期间接受积极化疗治疗的时间显著长于常规护理组，平均为 8.2 个月（范围 0 至 49 个月），而常规护理组为 6.3 个月（范围 0 至 41 个月），分别为（P = .002），中位数分别为 4.1 个月和 3.5 个月（P = .002）。
与常规护理相比，参与 STAR 组的急诊就诊率较低（1 年时为 34% vs 41%；P = .02；图 3）。这些差异在计算机经验不足的亚组中更为明显（34% vs 56%；P = .02），而在计算机经验丰富的亚组中则不明显（34% vs 36%；P = .16）。总体研究人群中，1 年内住院患者比例也呈现类似趋势（45% vs 49%；P = .08），计算机经验不足的亚组中差异更为显著且具有统计学意义（44% vs 63%；P = .003），而在计算机经验丰富的亚组中则无显著差异（46% vs 45%；P = .75；数据补充）。STAR 组患者在研究期间接受积极化疗治疗的时间显著长于常规护理组，平均为 8.2 个月（范围 0 至 49 个月），而常规护理组为 6.3 个月（范围 0 至 41 个月），分别为（P = .002），中位数分别为 4.1 个月和 3.5 个月（P = .002）。
图 3. 急诊室（ER）就诊的累积发生率。显示了患者访问 ER 的发生率，死亡作为竞争事件。(A) 所有患者；(B) 有计算机经验的患者；(C) 无计算机经验的患者。STAR，症状追踪与报告网络自报系统（研究干预措施）。
Overall and Quality-Adjusted Survival
总体和质量调整生存期
At 1 year, 69% of patients were alive in the usual-care arm compared with 75% with STAR, a difference of 6% (P = .05; Table 3). This difference was more pronounced among computer-inexperienced participants (60% vs. 74%; P = .02), with a trend seen among computer-experienced participants (71% v 76%; P = .45). Significant differences in quality-adjusted survival were observed during this 1-year period for all patients (mean of 8.0 v 8.7 months; P = .004) and were statistically significant in both subgroups.
在 1 年时，常规护理组中 69%的患者存活，而 STAR 组为 75%，差异为 6%（P = .05；表 3）。这种差异在计算机经验不足的参与者中更为明显（60% vs. 74%；P = .02），而在计算机经验丰富的参与者中则呈现趋势（71% vs. 76%；P = .45）。在这一年的期间内，所有患者在质量调整后的生存期方面观察到显著差异（平均 8.0 个月 vs. 8.7 个月；P = .004），并且在两个亚组中均具有统计学意义。
在 1 年时，常规护理组中 69%的患者存活，而 STAR 组为 75%，差异为 6%（P = .05；表 3）。这种差异在计算机经验不足的参与者中更为明显（60% vs. 74%；P = .02），而在计算机经验丰富的参与者中则呈现趋势（71% vs. 76%；P = .45）。在这一年的期间内，所有患者在质量调整后的生存期方面观察到显著差异（平均 8.0 个月 vs. 8.7 个月；P = .004），并且在两个亚组中均具有统计学意义。
| Patients 患者 | N | STAR (95% CI) STAR（95% CI） | Usual Care (95% CI) 常规护理（95% CI） | P (Univariable)* P（单变量）* | P (Multivariable)* P（多变量）* |
|---|---|---|---|---|---|
| Overall survival, % alive at 1 year 总体生存率，1 年生存率百分比 | |||||
| All patients 所有患者 | 766 | 75.1 (70.7 to 79.0) 75.1（70.7 至 79.0） | 68.6 (63.2 to 73.6) 68.6（63.2 至 73.6） | .03 | .05 |
| Subgroup analysis, % alive at 1 year 亚组分析，1 年生存率 | |||||
| Computer inexperienced 计算机经验不足 | 227 | 74.2 (66.6 to 80.9) 74.2（66.6 至 80.9） | 59.7 (47.5 to 71.1) 59.7（47.5 至 71.1） | .03 | .02 |
| Computer experienced 计算机经验丰富 | 539 | 75.5 (70.1 to 80.4) 75.5（70.1 至 80.4） | 71.1 (65.1 to 76.7) 71.1（65.1 至 76.7） | .25 | .45 |
| Quality-adjusted 12-month survival, months 质量调整后的 12 个月生存期，月数 | |||||
| All patients 所有患者 | 757† | 8.7 (8.3 to 9.0 ) 8.7（8.3 至 9.0） | 8.0 (7.6 to 8.4 ) 8.0（7.6 至 8.4） | .002 | .004 |
| Subgroup analysis, months 亚组分析，月份 | |||||
| Computer inexperienced 计算机新手 | 220† | 8.3 (7.8 to 8.8 ) 8.3（7.8 至 8.8） | 7.2 (6.3 to 8.2 ) 7.2（6.3 至 8.2） | .03 | .02 |
| Computer experienced 计算机经验丰富 | 537† | 8.8 (8.5 to 9.2 ) 8.8（8.5 至 9.2） | 8.2 (7.7 to 8.6 ) 8.2（7.7 至 8.6） | .02 | .046 |
Abbreviation: STAR, Symptom Tracking and Reporting web-based self-reporting system (study intervention).
*
P values for between-arm comparisons. Multivariable analyses controlled for age, sex, cancer type, race, and education level. For overall analyses, subgroup assignment (computer experienced or computer inexperienced) was also included as a covariate.
†
Participants with missing baseline health-related quality of life scores not included in quality-adjusted survival analysis.
Symptom Reporting and Nurse Responses to E-mail Alerts
症状报告与护士对电子邮件警报的响应
On average, 73% of participants assigned to the intervention arm completed a self-report at any given clinic visit (Data Supplement). A total of 84,212 individual symptoms were self-reported during the study. Among these, 1,431 or 1.7% were severe or disabling (grade 3 or 4), reported by 277 of the 441 (63%) intervention arm participants. The most common severe or disabling patient-reported symptoms were fatigue, pain, anorexia, dyspnea, neuropathy, and nausea. Nursing interventions taken in direct response to e-mail alerts included telephone counseling about symptom management (in response to 77% of alerts), supportive medication initiation/change (12%), referral to the ER/hospital (8%), chemotherapy dose modification (2%), and imaging/test orders (2%). No difference in the number of nursing calls to patients during participation was detected, with a mean of 12.8 in the STAR group vs. 12.9 in the control group (P = .93).
平均而言，73%的干预组参与者在任何一次诊所就诊时完成了自我报告（数据补充）。研究期间共自我报告了 84,212 个单独的症状。其中，1,431 个或 1.7%为严重或致残（3 级或 4 级），由 441 名干预组参与者中的 277 人（63%）报告。最常见的严重或致残患者报告症状包括疲劳、疼痛、厌食、呼吸困难、神经病变和恶心。直接响应电子邮件警报采取的护理干预措施包括关于症状管理的电话咨询（响应 77%的警报）、支持性药物的启动/更改（12%）、转诊至急诊/医院（8%）、化疗剂量调整（2%）以及影像/检查订单（2%）。在参与期间，护理人员对患者的电话呼叫次数没有差异，STAR 组平均为 12.8 次，对照组为 12.9 次（P = .93）。
平均而言，73%的干预组参与者在任何一次诊所就诊时完成了自我报告（数据补充）。研究期间共自我报告了 84,212 个单独的症状。其中，1,431 个或 1.7%为严重或致残（3 级或 4 级），由 441 名干预组参与者中的 277 人（63%）报告。最常见的严重或致残患者报告症状包括疲劳、疼痛、厌食、呼吸困难、神经病变和恶心。直接响应电子邮件警报采取的护理干预措施包括关于症状管理的电话咨询（响应 77%的警报）、支持性药物的启动/更改（12%）、转诊至急诊/医院（8%）、化疗剂量调整（2%）以及影像/检查订单（2%）。在参与期间，护理人员对患者的电话呼叫次数没有差异，STAR 组平均为 12.8 次，对照组为 12.9 次（P = .93）。
Discussion 讨论
For adults receiving outpatient chemotherapy for advanced cancer at a large specialty cancer center, web-based symptom reporting with automated clinician e-mail alerts resulted in better HRQL, fewer ER visits, fewer hospitalizations, a longer duration of palliative chemotherapy, and superior quality-adjusted survival.
对于在大型专科癌症中心接受晚期癌症门诊化疗的成人患者，基于网络的症状报告与自动化的临床医生电子邮件提醒相结合，可改善生活质量（HRQL），减少急诊室就诊次数，降低住院率，延长姑息性化疗的持续时间，并提高质量调整后的生存率。
对于在大型专科癌症中心接受晚期癌症门诊化疗的成人患者，基于网络的症状报告与自动化的临床医生电子邮件提醒相结合，可改善生活质量（HRQL），减少急诊室就诊次数，降低住院率，延长姑息性化疗的持续时间，并提高质量调整后的生存率。
Although the vast majority of patient-reported symptoms were grade 1 or 2 (mild to moderate), more than 1,400 were grade 3 or 4 (severe to disabling). In response to e-mail alerts for severe or worsening symptoms, nurses performed direct interventions primarily composed of telephone counseling, medication changes, and ER or hospital referral. Clinical actions may also have been taken in response to symptom reports delivered to clinicians at each office visit including responses to mild/moderate symptoms, although these were not systematically tracked and may be a useful focus of future research.
尽管绝大多数患者报告的症状为 1 级或 2 级（轻度至中度），但超过 1,400 例为 3 级或 4 级（重度至致残）。针对严重或恶化的症状发出的电子邮件警报，护士们主要通过电话咨询、药物调整以及急诊或住院转诊等方式进行直接干预。临床行动也可能在每次就诊时针对症状报告作出响应，包括对轻度/中度症状的响应，尽管这些并未系统跟踪，但可能是未来研究的有益焦点。
尽管绝大多数患者报告的症状为 1 级或 2 级（轻度至中度），但超过 1,400 例为 3 级或 4 级（重度至致残）。针对严重或恶化的症状发出的电子邮件警报，护士们主要通过电话咨询、药物调整以及急诊或住院转诊等方式进行直接干预。临床行动也可能在每次就诊时针对症状报告作出响应，包括对轻度/中度症状的响应，尽管这些并未系统跟踪，但可能是未来研究的有益焦点。
Prior studies have explored mechanisms by which patient reporting of symptoms may confer clinical benefits, with findings including increased rates of symptom discussions between patients and clinicians,11,18,19 intensified symptom management by clinicians in response to patient reports,11-13 and improved symptom control when patient reports are shared with clincians.11-14,18 As such, systematic patient reporting appears to enhance clinician awareness and can augment existing mechanisms for symptom management during routine oncology care. Conversely, when undetected in the absence of patient self-reporting, symptoms may continue to worsen and cause serious complications, lead to hospital visits, limit the ability to safely deliver chemotherapy, and diminish outcomes, as observed in this study.
先前的研究探讨了患者报告症状可能带来的临床益处机制，研究结果包括患者与临床医生之间症状讨论频率的增加， 11,18,19 临床医生根据患者报告加强症状管理， 11-13 以及当患者报告与临床医生共享时症状控制的改善。 11-14,18 因此，系统的患者报告似乎能提高临床医生的意识，并能增强现有机制在常规肿瘤治疗期间的症状管理。相反，在没有患者自我报告的情况下未被发现的症状可能会持续恶化，导致严重并发症，增加住院次数，限制安全进行化疗的能力，并降低治疗效果，正如本研究所观察到的。
先前的研究探讨了患者报告症状可能带来的临床益处机制，研究结果包括患者与临床医生之间症状讨论频率的增加， 11,18,19 临床医生根据患者报告加强症状管理， 11-13 以及当患者报告与临床医生共享时症状控制的改善。 11-14,18 因此，系统的患者报告似乎能提高临床医生的意识，并能增强现有机制在常规肿瘤治疗期间的症状管理。相反，在没有患者自我报告的情况下未被发现的症状可能会持续恶化，导致严重并发症，增加住院次数，限制安全进行化疗的能力，并降低治疗效果，正如本研究所观察到的。
This randomized trial should be interpreted in the context of three key limitations. First, it was conducted at a single, urban tertiary care cancer center limiting generalizability. However, inclusion of a computer-inexperienced subgroup, with 39% having no education beyond high school, suggests its applicability to diverse US cancer populations. The study included only English speakers; future assessments should include additional languages and nontext interfaces, such as interactive voice response. ER and hospital admissions regardless of primary site were tracked based on the institution’s electronic medical record system. However, some admissions to outside institutions may not have been recorded.
这项随机试验应在其三个关键局限性的背景下进行解读。首先，该研究仅在一所城市三级癌症中心进行，限制了其普遍适用性。然而，纳入了一个计算机经验不足的亚组，其中 39%的人仅受过高中以上教育，这表明其适用于美国多样化的癌症人群。研究仅包括英语使用者；未来的评估应纳入其他语言和非文本界面，如交互式语音响应。根据机构的电子病历系统，无论原发部位如何，均追踪了急诊和住院情况。然而，某些转诊至外部机构的住院记录可能未被记录。
这项随机试验应在其三个关键局限性的背景下进行解读。首先，该研究仅在一所城市三级癌症中心进行，限制了其普遍适用性。然而，纳入了一个计算机经验不足的亚组，其中 39%的人仅受过高中以上教育，这表明其适用于美国多样化的癌症人群。研究仅包括英语使用者；未来的评估应纳入其他语言和非文本界面，如交互式语音响应。根据机构的电子病历系统，无论原发部位如何，均追踪了急诊和住院情况。然而，某些转诊至外部机构的住院记录可能未被记录。
Second, we chose to use the EQ-5D assessment of overall HRQL rather than more granular questionnaires that evaluate particular symptoms in detail. We selected this approach to avoid conflating the intervention with the outcome metric and to enable calculation of quality-adjusted survival. As a result, we have limited information about which symptoms were best addressed by symptom reporting. Despite the generic nature of the EQ-5D measure, significant and clinically meaningful differences were observed between study arms.
其次，我们选择使用 EQ-5D 评估整体健康相关生活质量（HRQL），而不是更细致的问卷来详细评估特定症状。我们选择这种方法是为了避免将干预措施与结果指标混淆，并便于计算质量调整生存期。因此，我们对于哪些症状通过症状报告得到了最佳处理的信息有限。尽管 EQ-5D 量表具有通用性，但在研究组之间观察到了显著且具有临床意义的差异。
其次，我们选择使用 EQ-5D 评估整体健康相关生活质量（HRQL），而不是更细致的问卷来详细评估特定症状。我们选择这种方法是为了避免将干预措施与结果指标混淆，并便于计算质量调整生存期。因此，我们对于哪些症状通过症状报告得到了最佳处理的信息有限。尽管 EQ-5D 量表具有通用性，但在研究组之间观察到了显著且具有临床意义的差异。
Third, substantial numbers of participants did not have 6-month HRQL data available because they had died or discontinued treatment. The survival and utilization endpoints would not be affected by these missing data, and HRQL results were similar in multiple sensitivity analyses. Moreover, missing HRQL would be more likely expected to attenuate detection of potential benefits of PRO reporting because of informative censoring of scores when patients died or discontinued treatment earlier in the usual care arm who otherwise might have reported low HRQL scores.38 Nonetheless, earlier or more frequent systematic outcomes data collection is warranted for future assessments. The study design did not anticipate the observed level of attrition in the accrual plan.
第三，大量参与者没有可用的 6 个月 HRQL 数据，因为他们已经去世或停止了治疗。这些缺失数据不会影响生存和利用率终点，并且在多次敏感性分析中，HRQL 结果相似。此外，由于患者在常规护理组中较早死亡或停止治疗，可能会导致 HRQL 评分信息性删失，因此缺失的 HRQL 更有可能减弱对 PRO 报告潜在益处的检测。 38 尽管如此，未来评估中仍需更早或更频繁地系统收集结果数据。研究设计并未预见到入组计划中观察到的流失水平。
第三，大量参与者没有可用的 6 个月 HRQL 数据，因为他们已经去世或停止了治疗。这些缺失数据不会影响生存和利用率终点，并且在多次敏感性分析中，HRQL 结果相似。此外，由于患者在常规护理组中较早死亡或停止治疗，可能会导致 HRQL 评分信息性删失，因此缺失的 HRQL 更有可能减弱对 PRO 报告潜在益处的检测。 38 尽管如此，未来评估中仍需更早或更频繁地系统收集结果数据。研究设计并未预见到入组计划中观察到的流失水平。
Some benefits appeared greater for computer-inexperienced patients, who were overall older, frailer, and more symptomatic than computer-experienced patients. Participants lacking computer experience may have less-developed health communication skills and thereby benefit more from a structured program for eliciting symptoms. Future work is warranted to discern which patient populations may benefit most from this type of health communication intervention.
对于计算机经验较少的患者，其整体年龄较大、身体较虚弱且症状更明显，因此受益更多。缺乏计算机经验的参与者可能健康沟通技能较为欠缺，从而更能从结构化的症状引出程序中获益。未来有必要进一步研究，以确定哪些患者群体最可能从这种健康沟通干预中获益。
对于计算机经验较少的患者，其整体年龄较大、身体较虚弱且症状更明显，因此受益更多。缺乏计算机经验的参与者可能健康沟通技能较为欠缺，从而更能从结构化的症状引出程序中获益。未来有必要进一步研究，以确定哪些患者群体最可能从这种健康沟通干预中获益。
A formal cost-utility analysis was not performed. Resource use was relatively modest and included software development, server space and maintenance, eight tablet computers, and time spent by patients and clinicians to report and review symptoms and to respond when they were severe or worsening. The software did not provide recommendations to patients or clinicians about management of detected symptoms, which could be added in future systems.
未进行正式的成本效用分析。资源使用相对有限，包括软件开发、服务器空间和维护、八台平板电脑，以及患者和临床医生用于报告和审查症状以及在症状严重或恶化时做出响应的时间。该软件未向患者或临床医生提供关于检测到的症状管理的建议，未来系统中可添加此功能。
未进行正式的成本效用分析。资源使用相对有限，包括软件开发、服务器空间和维护、八台平板电脑，以及患者和临床医生用于报告和审查症状以及在症状严重或恶化时做出响应的时间。该软件未向患者或临床医生提供关于检测到的症状管理的建议，未来系统中可添加此功能。
In the context of a changing health care delivery system where both population management and patient centeredness are prioritized, symptom self-reporting engages patients as active participants and may improve the experience, efficiency, and outcomes of care. Given the favorable outcomes we have demonstrated with a simple prototype, further work to refine optimal strategies for engaging both patients and clinicians in harnessing technology to improve care should be a priority.
在不断变化的医疗保健交付系统中，人口管理和以患者为中心的优先级日益凸显，症状自我报告使患者成为积极参与者，并可能改善护理的体验、效率和效果。鉴于我们通过简单原型展示的有利结果，进一步优化策略以促进患者和临床医生利用技术改善护理的工作应成为优先事项。
在不断变化的医疗保健交付系统中，人口管理和以患者为中心的优先级日益凸显，症状自我报告使患者成为积极参与者，并可能改善护理的体验、效率和效果。鉴于我们通过简单原型展示的有利结果，进一步优化策略以促进患者和临床医生利用技术改善护理的工作应成为优先事项。
Acknowledgment 致谢
We thank the study participants and the many physicians and nurses who reviewed and responded to symptom reports; Kai Lin, Charmaine Pun, and Kevin Shannon for technical work developing the STAR patient self-report web platform; Hojin Yang for statistical programming support; and Colin Begg, PhD, for programmatic support of this study. We also thank this study’s clinical research associates and data managers, Narre Heon, Dawn Lavene, Sean Ryan, Mary Shaw, and Liora Stark. Peter Bach, MD, Bryce Reeve, PhD, and Thomas Stinchcombe, MD, provided valuable feedback on the manuscript.
我们感谢研究参与者和许多审阅并回应症状报告的医生和护士；Kai Lin、Charmaine Pun 和 Kevin Shannon 在开发 STAR 患者自我报告网络平台方面的技术工作；Hojin Yang 提供的统计编程支持；以及 Colin Begg 博士为本研究提供的程序支持。我们还感谢本研究的临床研究助理和数据管理人员 Narre Heon、Dawn Lavene、Sean Ryan、Mary Shaw 和 Liora Stark。Peter Bach 博士、Bryce Reeve 博士和 Thomas Stinchcombe 博士对稿件提供了宝贵的反馈意见。
我们感谢研究参与者和许多审阅并回应症状报告的医生和护士；Kai Lin、Charmaine Pun 和 Kevin Shannon 在开发 STAR 患者自我报告网络平台方面的技术工作；Hojin Yang 提供的统计编程支持；以及 Colin Begg 博士为本研究提供的程序支持。我们还感谢本研究的临床研究助理和数据管理人员 Narre Heon、Dawn Lavene、Sean Ryan、Mary Shaw 和 Liora Stark。Peter Bach 博士、Bryce Reeve 博士和 Thomas Stinchcombe 博士对稿件提供了宝贵的反馈意见。
See accompanying editorial on page 527
参见第 527 页的随附社论
参见第 527 页的随附社论
The National Cancer Institute and the Steps for Breath Fund of Memorial Sloan Kettering Cancer Center did not play any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
美国国家癌症研究所和纪念斯隆·凯特琳癌症中心的呼吸基金在研究的设计和实施、数据的收集、管理、分析和解释、手稿的准备、审查或批准，或决定提交手稿发表等方面没有任何作用。
美国国家癌症研究所和纪念斯隆·凯特琳癌症中心的呼吸基金在研究的设计和实施、数据的收集、管理、分析和解释、手稿的准备、审查或批准，或决定提交手稿发表等方面没有任何作用。
Clinical trial information: NCT00578006.
临床试验信息：NCT00578006。
临床试验信息：NCT00578006。
The summary of supplementary materials could not be included.
无法包含补充材料的摘要。
无法包含补充材料的摘要。
Supplementary Material 补充材料
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Authors’ Disclosures of Potential Conflicts of Interest
作者潜在利益冲突的披露
Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial
常规癌症治疗期间基于患者报告结果的症状监测：一项随机对照试验
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or jco.ascopubs.org/site/ifc.
以下是本手稿作者提供的披露信息。所有关系均被视为有偿。除非另有说明，否则关系为本人持有。I = 直系亲属，Inst = 我的机构。这些关系可能与本手稿的主题无关。有关 ASCO 利益冲突政策的更多信息，请访问 www.asco.org/rwc 或 jco.ascopubs.org/site/ifc。
以下是本手稿作者提供的披露信息。所有关系均被视为有偿。除非另有说明，否则关系为本人持有。I = 直系亲属，Inst = 我的机构。这些关系可能与本手稿的主题无关。有关 ASCO 利益冲突政策的更多信息，请访问 www.asco.org/rwc 或 jco.ascopubs.org/site/ifc。
Ethan Basch 伊森·巴什
Other Relationship: Journal of the American Medical Association, Patient-Centered Outcomes Research Institute
其他关系：美国医学会杂志，患者中心结果研究所
其他关系：美国医学会杂志，患者中心结果研究所
Allison M. Deal 艾莉森·M·迪尔
No relationship to disclose
无须披露的关系
无须披露的关系
Mark G. Kris 马克·G·克里斯
Consulting or Advisory Role: AstraZeneca, ARIAD Pharmaceuticals, Genentech, Daiichi Sankyo, Threshold Pharmaceuticals, Array BioPharma
咨询或顾问角色：阿斯利康、ARIAD 制药、基因泰克、第一三共、阈值制药、Array BioPharma
咨询或顾问角色：阿斯利康、ARIAD 制药、基因泰克、第一三共、阈值制药、Array BioPharma
Research Funding: Puma Biotechnology, Pfizer
研究资助：Puma Biotechnology，辉瑞
研究资助：Puma Biotechnology，辉瑞
Howard I. Scher 霍华德·I·谢尔
Consulting or Advisory Role: AstraZeneca, Astellas Pharma, Bristol-Myers Squibb, Endocyte, Ferring Pharmaceuticals, Genentech, OncologySTAT, Palmetto GBA, Pfizer, Sanofi, Takeda Pharmaceuticals, WIRB-Copernicus Group, Medivation, BIND Therapeutics, Janssen, Chugai Pharmaceutical, Blue Earth Diagnostics
咨询或顾问角色：阿斯利康、安斯泰来制药、百时美施贵宝、Endocyte、Ferring Pharmaceuticals、基因泰克、OncologySTAT、Palmetto GBA、辉瑞、赛诺菲、武田制药、WIRB-Copernicus Group、Medivation、BIND Therapeutics、杨森制药、中外制药、Blue Earth Diagnostics
咨询或顾问角色：阿斯利康、安斯泰来制药、百时美施贵宝、Endocyte、Ferring Pharmaceuticals、基因泰克、OncologySTAT、Palmetto GBA、辉瑞、赛诺菲、武田制药、WIRB-Copernicus Group、Medivation、BIND Therapeutics、杨森制药、中外制药、Blue Earth Diagnostics
Speakers’ Bureau: WebMD 演讲者局：WebMD
Research Funding: BIND Biosciences, Exelixis, Janssen Pharmaceuticals, Medivation, Janssen Diagnostics, Innocrin Pharmaceuticals
研究资助：BIND 生物科学公司、Exelixis 公司、杨森制药公司、Medivation 公司、杨森诊断公司、Innocrin 制药公司
研究资助：BIND 生物科学公司、Exelixis 公司、杨森制药公司、Medivation 公司、杨森诊断公司、Innocrin 制药公司
Travel, Accommodations, Expenses: Janssen Pharmaceuticals, Sanofi, Endocyte, AstraZeneca, Genentech, Bristol-Myers Squibb, Pfizer, Takeda Pharmaceuticals, Ferring, WIRB-Copernicus Group, Astellas Pharma, BIND Therapeutics, Celgene, Astellas Pharma
旅行、住宿、费用：杨森制药、赛诺菲、Endocyte、阿斯利康、基因泰克、百时美施贵宝、辉瑞、武田制药、Ferring、WIRB-Copernicus 集团、安斯泰来制药、BIND Therapeutics、新基、安斯泰来制药
旅行、住宿、费用：杨森制药、赛诺菲、Endocyte、阿斯利康、基因泰克、百时美施贵宝、辉瑞、武田制药、Ferring、WIRB-Copernicus 集团、安斯泰来制药、BIND Therapeutics、新基、安斯泰来制药
Clifford A. Hudis 克利福德·A·赫迪斯
Consulting or Advisory Role: Novartis, Genentech, Pfizer
咨询或顾问角色：诺华、基因泰克、辉瑞
咨询或顾问角色：诺华、基因泰克、辉瑞
Paul Sabbatini 保罗·萨巴蒂尼
Research Funding: Janssen Oncology, Bristol-Myers Squibb
研究资助：杨森肿瘤学，百时美施贵宝
研究资助：杨森肿瘤学，百时美施贵宝
Lauren Rogak 劳伦·罗加克
No relationship to disclose
无须披露的关系
无须披露的关系
Antonia V. Bennett 安东尼娅·V·贝内特
No relationship to disclose
无须披露的关系
无须披露的关系
Amylou Dueck 艾米露·杜克
No relationship to disclose
无须披露的关系
无须披露的关系
Thomas M. Atkinson 托马斯·M·阿特金森
No relationship to disclose
无关系披露
无关系披露
Joanne F. Chou 周乔安
No relationship to disclose
无须披露的关系
无须披露的关系
Dorothy Dulko 多萝西·杜尔科
No relationship to disclose
无须披露的关系
无须披露的关系
Laura Sit 劳拉·席特
No relationship to disclose
无须披露的关系
无须披露的关系
Allison Barz 艾莉森·巴兹
No relationship to disclose
无须披露的关系
无须披露的关系
Paul Novotny 保罗·诺沃特尼
No relationship to disclose
无须披露的关系
无须披露的关系
Michael Fruscione 迈克尔·弗鲁斯乔内
No relationship to disclose
无关系披露
无关系披露
Jeff A. Sloan 杰夫·A·斯隆
No relationship to disclose
无关系披露
无关系披露
Deborah Schrag 黛博拉·施拉格
Consulting or Advisory Role: New Century Health, Ohio State University
咨询或顾问角色：新世纪健康，俄亥俄州立大学
咨询或顾问角色：新世纪健康，俄亥俄州立大学
Other Relationship: Journal of the American Medical Association
其他关系：美国医学会杂志
其他关系：美国医学会杂志
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Information & Authors
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© 2015 by American Society of Clinical Oncology.
History
Published online: December 07, 2015
Published in print: February 20, 2016
Authors
Author Contributions
Conception and design: Ethan Basch, Deborah Schrag
Administrative support: Lauren Rogak, Michael Fruscione
Provision of study materials or patients: Ethan Basch, Mark G. Kris, Howard I. Scher, Clifford A. Hudis, Paul Sabbatini
Collection and assembly of data: Ethan Basch, Mark G. Kris, Howard I. Scher, Clifford A. Hudis, Paul Sabbatini, Lauren Rogak, Antonia V. Bennett, Dorothy Dulko, Laura Sit, Allison Barz, Michael Fruscione, Deborah Schrag
Data analysis and interpretation: Ethan Basch, Allison M. Deal, Lauren Rogak, Antonia V. Bennett, Amylou Dueck, Thomas M. Atkinson, Joanne F. Chou, Paul Novotny, Jeff A. Sloan, Deborah Schrag
Manuscript writing: All authors
Final approval of manuscript: All authors
Disclosures
Authors’ disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.
Funding Information
Supported by the National Cancer Institute and a grant from the Society of Memorial Sloan Kettering.
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Article Citation
Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial. JCO 34, 557-565(2016).
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Ethan Basch, Allison M. Deal, Mark G. Kris, Howard I. Scher, Clifford A. Hudis, Paul Sabbatini, Lauren Rogak, Antonia V. Bennett, Amylou C. Dueck, Thomas M. Atkinson, Joanne F. Chou, Dorothy Dulko, Laura Sit, Allison Barz, Paul Novotny, Michael Fruscione, Jeff A. Sloan, Deborah Schrag
Journal of Clinical Oncology 2016 34:6, 557-565
Ethan Basch, Allison M. Deal, Mark G. Kris, Howard I. Scher, Clifford A. Hudis, Paul Sabbatini, Lauren Rogak, Antonia V. Bennett, Amylou C. Dueck, Thomas M. Atkinson, Joanne F. Chou, Dorothy Dulko, Laura Sit, Allison Barz, Paul Novotny, Michael Fruscione, Jeff A. Sloan, Deborah Schrag
Journal of Clinical Oncology 2016 34:6, 557-565
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Tables
| Characteristic | All Patients (N = 766) | Computer-Experienced Subgroup (n = 539) | Computer-Inexperienced Subgroup (n = 227)* | |||
|---|---|---|---|---|---|---|
| STAR (n = 441) | Usual Care (n = 325) | STAR (n = 286) | Usual Care (n = 253) | STAR (n = 155) | Usual Care (n = 72) | |
| Age, median (range), years | 61 (30-91) | 62 (26-88) | 59 (30-85) | 60 (26-88) | 67 (38-91) | 67 (44-86) |
| Female sex | 257 (58) | 187 (58) | 184 (64) | 152 (60) | 73 (47) | 35 (49) |
| Race | ||||||
| White | 377 (86) | 283 (87) | 253 (89) | 230 (91) | 124 (80) | 53 (74) |
| Black† | 43 (10) | 24 (7) | 20 (7) | 10 (4) | 23 (15) | 14 (19) |
| Asian | 21 (5) | 18 (6) | 13 (5) | 13 (5) | 8 (5) | 5 (7) |
| Cancer type | ||||||
| Genitourinary | 143 (32) | 102 (31) | 78 (27) | 77 (30) | 65 (42) | 25 (35) |
| Gynecologic | 97 (22) | 80 (25) | 67 (23) | 66 (26) | 30 (19) | 14 (19) |
| Breast | 89 (20) | 54 (17) | 72 (25) | 47 (19) | 17 (11) | 7 (10) |
| Lung | 112 (25) | 89 (27) | 69 (24) | 63 (25) | 43 (28) | 26 (36) |
| Education | ||||||
| High school or less | 106 (24) | 64 (20) | 46 (16) | 36 (14) | 60 (39) | 28 (39) |
| College | 205 (47) | 155 (48) | 143 (50) | 125 (49) | 62 (40) | 30 (42) |
| Graduate degree | 130 (30) | 106 (33) | 97 (34) | 92 (36) | 33 (21) | 14 (19) |
| HRQL‡ | ||||||
| Mean | 0.85 | 0.84 | 0.86 | 0.85 | 0.82 | 0.84 |
| Range | 0.27-1.0 | 0.20-1.00 | 0.33-1.00 | 0.22-1.00 | 0.27-1.00 | 0.20-1.00 |
| Days since initiation of chemotherapy | ||||||
| Mean | 46 | 40 | 44 | 41 | 51 | 39 |
| Range | 0-1,025 | 0-840 | 0-511 | 0-840 | 0-1,025 | 0-427 |
NOTE. Data presented as No. (%) unless otherwise noted. No significant differences between study arms were seen for any of the baseline characteristics in the study population overall or within either of the subgroups (all P > .3).
Abbreviations: HRQL, health related quality of life; STAR, Symptom Tracking and Reporting web-based self-reporting system (study intervention).
*
Randomized 2:1 in this subgroup.
†
Includes four patients categorized as “other” at enrollment and determined by chart review to have black race.
‡
HRQL measured via the EuroQoL EQ-5D questionnaire.
| Patients | N* | STAR (n = 277) | Usual Care (n = 180) | P (Univariable)† | P (Multivariable)† | Effect Size |
|---|---|---|---|---|---|---|
| Evaluable patients* | 457 | |||||
| EQ-5D at baseline | 86.2 (84.7 to 87.7) | 86.6 (84.7 to 88.5) | ||||
| EQ-5D at 6 months | 84.8 (83.2 to 86.4) | 79.5 (76.7 to 82.2) | ||||
| Point drop from baseline | 1.4 (0.4 to 3.1) | 7.1 (4.8 to 9.5) | ||||
| Difference in point drop between arms | 5.7 | <.001 | <.001 | 0.37 | ||
| Subgroup analysis | ||||||
| Computer-inexperienced subgroup* | 116 | |||||
| EQ-5D at baseline | 83.6 (80.2 to 86.9) | 86.9 (81.9 to 91.9) | ||||
| EQ-5D at 6 months | 81.8 (78.2 to 85.3) | 78.6 (71.2 to 86.0) | ||||
| Point drop from baseline | 1.8 ( to 2.1 to 5.7) | 8.3 (3.6 to 13.1) | ||||
| Difference in point drop between arms | 6.5 | .06 | .11 | 0.38 | ||
| Computer-experienced subgroup* | 341 | |||||
| EQ-5D at baseline | 87.3 (85.7 to 88.6) | 86.5 (84.5 to 88.6) | ||||
| EQ-5D at 6 months | 86.1 (84.3 to 87.8) | 79.7 (76.7 to 82.7) | ||||
| Point drop from baseline | 1.2 (0.7 to 3.1) | 6.9 (4.2 to 9.5) | ||||
| Difference in point drop between arms | 5.7 | <.001 | <.001 | 0.38 | ||
NOTE. Data presented as mean (95% CI) unless otherwise noted.
Abbreviations: STAR, Symptom Tracking and Reporting web-based self-reporting system; EQ-5D, EuroQoL EQ-5D quality of life questionnaire.
*
Patents without postbaseline EQ-5D scores were not included in the primary health-related quality of life analysis but were included in the sensitivity analysis with similar results.
†
P values for between-arm comparisons. Multivariable analyses controlled for age, sex, cancer type, race, and education level. For overall analyses, subgroup assignment (computer experienced or computer inexperienced) was also included as a covariate.
| Patients | N | STAR (95% CI) | Usual Care (95% CI) | P (Univariable)* | P (Multivariable)* |
|---|---|---|---|---|---|
| Overall survival, % alive at 1 year | |||||
| All patients | 766 | 75.1 (70.7 to 79.0) | 68.6 (63.2 to 73.6) | .03 | .05 |
| Subgroup analysis, % alive at 1 year | |||||
| Computer inexperienced | 227 | 74.2 (66.6 to 80.9) | 59.7 (47.5 to 71.1) | .03 | .02 |
| Computer experienced | 539 | 75.5 (70.1 to 80.4) | 71.1 (65.1 to 76.7) | .25 | .45 |
| Quality-adjusted 12-month survival, months | |||||
| All patients | 757† | 8.7 (8.3 to 9.0 ) | 8.0 (7.6 to 8.4 ) | .002 | .004 |
| Subgroup analysis, months | |||||
| Computer inexperienced | 220† | 8.3 (7.8 to 8.8 ) | 7.2 (6.3 to 8.2 ) | .03 | .02 |
| Computer experienced | 537† | 8.8 (8.5 to 9.2 ) | 8.2 (7.7 to 8.6 ) | .02 | .046 |
Abbreviation: STAR, Symptom Tracking and Reporting web-based self-reporting system (study intervention).
*
P values for between-arm comparisons. Multivariable analyses controlled for age, sex, cancer type, race, and education level. For overall analyses, subgroup assignment (computer experienced or computer inexperienced) was also included as a covariate.
†
Participants with missing baseline health-related quality of life scores not included in quality-adjusted survival analysis.
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