Affiliations of authors: Division of Cancer Prevention and Control, Department of Internal Medicine, College of Medicine, Comprehensive Cancer Center (EDP), and Center for Biostatistics (GSY), The Ohio State University, Columbus, OH; Institute for Clinical Research and Health Policy Studies, Tufts Medical Center and Tufts University School of Medicine, Boston, MA (KMF); Women's Health Unit, Section of General Internal Medicine, Evans Department of Medicine, Boston Medical Center and Women's Health Interdisciplinary Research Center, Boston University School of Medicine, Boston, MA (TAB); Division of Health Policy and Administration, School of Public Health, University of Illinois at Chicago, Chicago, IL (EC, JSD); Department of Obstetrics and Gynecology, University of Texas Health Science Center, San Antonio, TX (DLD); Department of Family Medicine and Public Health Sciences and Wilmot Cancer Center, University of Rochester Medical Center, Rochester, NY (KF); Center to Reduce Cancer Health Disparities, National Cancer Institute (MLH), and Biostatistics and Bioinformatics Branch, Division of Epidemiology, Statistics, and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (DMM), Rockville, MD (MLH); George Washington University School of Public Health and Health Services, Washington, DC (NL, PL); H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL (J-HL, RGR); George Washington Cancer Institute, Washington, DC (PL. SRP); Duke Cancer Institute, Durham, NC (SRP); Denver Health, Denver, CO (PCR, EMW); University of Colorado Denver, Aurora, CO (PCR); Department of Family Medicine, University of South Florida, Tampa, FL (RGR); Department of Obstetrics and Gynecology and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (MS); Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL (MS); Clinical Research Ser
J Natl Cancer Inst. 2014 Jun 17;106(6):dju115. doi: 10.1093/jnci/dju115. Print 2014 Jun.
Patient navigation is a promising intervention to address cancer disparities but requires a multisite controlled trial to assess its effectiveness.
The Patient Navigation Research Program compared patient navigation with usual care on time to diagnosis or treatment for participants with breast, cervical, colorectal, or prostate screening abnormalities and/or cancers between 2007 and 2010. Patient navigators developed individualized strategies to address barriers to care, with the focus on preventing delays in care. To assess timeliness of diagnostic resolution, we conducted a meta-analysis of center- and cancer-specific adjusted hazard ratios (aHRs) comparing patient navigation vs usual care. To assess initiation of cancer therapy, we calculated a single aHR, pooling data across all centers and cancer types. We conducted a metaregression to evaluate variability across centers. All statistical tests were two-sided.
The 10521 participants with abnormal screening tests and 2105 with a cancer or precancer diagnosis were predominantly from racial/ethnic minority groups (73%) and publically insured (40%) or uninsured (31%). There was no benefit during the first 90 days of care, but a benefit of navigation was seen from 91 to 365 days for both diagnostic resolution (aHR = 1.51; 95% confidence interval [CI] = 1.23 to 1.84; P < .001)) and treatment initiation (aHR = 1.43; 95% CI = 1.10 to 1.86; P < .007). Metaregression revealed that navigation had its greatest benefits within centers with the greatest delays in follow-up under usual care.
Patient navigation demonstrated a moderate benefit in improving timely cancer care. These results support adoption of patient navigation in settings that serve populations at risk of being lost to follow-up.
患者导航是一种有前途的干预措施，可以解决癌症差异问题，但需要进行多站点对照试验来评估其效果。
患者导航研究计划于 2007 年至 2010 年期间，将患者导航与常规护理进行比较，比较参与者的乳腺、宫颈、结直肠或前列腺筛查异常和/或癌症的诊断或治疗时间。患者导航员制定了个性化的策略来解决护理障碍，重点是防止护理延迟。为了评估诊断结果的及时性，我们对中心和癌症特异性调整后的危险比（aHR）进行了荟萃分析，比较了患者导航与常规护理。为了评估癌症治疗的启动，我们计算了一个单一的 aHR，汇集了所有中心和癌症类型的数据。我们进行了荟萃回归分析，以评估中心之间的变异性。所有统计检验均为双侧检验。
10521 名有异常筛查试验的参与者和 2105 名有癌症或癌前病变诊断的参与者主要来自少数族裔群体（73%）和公共保险（40%）或无保险（31%）。在护理的头 90 天内没有获益，但在 91 至 365 天内，导航对诊断结果的改善（aHR = 1.51；95%置信区间[CI] = 1.23 至 1.84；P <.001）和治疗启动（aHR = 1.43；95% CI = 1.10 至 1.86；P <.007）都有获益。荟萃回归显示，在常规护理中随访延迟最大的中心内，导航的获益最大。
患者导航在改善及时癌症护理方面显示出适度的益处。这些结果支持在为可能失去随访的人群服务的环境中采用患者导航。
