Physicians’ Use of Patients’ Daily Reports of Quality of Life to Evaluate Treatment Response in Phase I Cancer Trials


For cancer patients on Phase I trials, one of the most important physician decisions is whether or not patients are deriving benefit from therapy. With an increasing number of cytostatic treatment agents, the criteria to determine patient response to Phase I treatment has become harder to define. Physicians are increasingly looking to patient-reported outcomes (PROs) such as quality of life (QOL) to help evaluate treatment response. Electronic daily diary (EDD) devices can be used by patients to report their QOL over extended periods of time, thereby providing a more accurate picture of how patients are affected by treatment on a daily basis. However, questions remain about how to integrate this patient-reported information into decisions about Phase I treatment. This study investigated how physicians use patients’ daily QOL reports to evaluate patient response to Phase I treatment. Data were collected over a 4-month period from Phase I patients (N = 30) and physicians (N = 3) in an NCI-designated comprehensive cancer center. Patients completed daily QOL reports using EDD devices and physicians were provided with a summary of patients’ QOL before each visit. After the visit, doctors recorded their treatment decision and also rated the importance of four biomedical factors (Toxicity, Imaging, Labs, and Performance Status) and QOL in their treatment decision for that visit. Although physicians rated QOL as being very important in evaluating treatment response, in practice, when predictors of their decisions were analyzed, results showed they relied exclusively on biomedical data (Toxicity, Imaging) to make Phase I treatment decisions. Questions remain about the utility and effective integration of QOL and biomedical data in clinical decision-making processes in Phase I clinical trials.

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F. W. K. Harper, E. I. Heath, M. E. J. Gleason, L. Penner, P. LoRusso, D. Wang and T. L. Albrecht, "Physicians’ Use of Patients’ Daily Reports of Quality of Life to Evaluate Treatment Response in Phase I Cancer Trials," Journal of Cancer Therapy, Vol. 3 No. 5, 2012, pp. 582-588. doi: 10.4236/jct.2012.35074.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] C. Acquadro, et al., “Incorporating the Patient’s Perspective into Drug Development and Communication: An Ad Hoc Task Force Report of the Patient-Reported Outcomes (PRO) Harmonization Group Meeting at the Food and Drug Administration,” Value Health, Vol. 6, No. 5, 2003, pp. 522-531. doi:10.1046/j.1524-4733.2003.65309.x
[2] D. L. Fairclough, “Patient Reported Outcomes as Endpoints in Medical Research,” Statistical Methods in Medical Research, Vol. 13, No. 2, 2004, pp. 115-138. doi:10.1191/0962280204sm357ra
[3] A. O’Mara, “CCOP Perspective on the FDA PRO Guidance: What Does It Mean for NCI-Sponsored Cancer Control Trials in FDA Guidance on Patient Reported Outcomes—Discussion, Dissemination, and Operationalization,” Chantilly, 2006.
[4] D. B. A. Osaba, M. D. Brundage, et al., “Evaluating Health-Related Quality of Life in Cancer Clinical Trials: The National Cancer Institute of Canada Clinical Trials Group Experience,” Chantilly, 2006.
[5] US Department of Health and Human Services, F.D.A., “Guidance for Industry: Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims,” US Department of Health and Human Services, F.D.A., Washington DC, 2006.
[6] P. Therasse, et al., “New Guidelines to Evaluate the Response to Treatment in Solid Tumors,” Journal of the National Cancer Institute, Vol. 92, No. 3, 2000, pp. 205-216. doi:10.1093/jnci/92.3.205
[7] E. D. Hacker and C. E. Ferrans, “Ecological Momentary Assessment of Fatigue in Patients Receiving Intensive Cancer Therapy,” Journal of Pain Symptom Management, Vol. 33, No. 3, 2007, pp. 267-275. doi:10.1016/j.jpainsymman.2006.08.007
[8] S. Wolpin, et al., “Acceptability of an Electronic Self-Report Assessment Program for Patients with Cancer,” Computers, Informatics, Nursing, Vol. 26, No. 6, 2008, pp. 332-338. doi:10.1097/01.NCN.0000336464.79692.6a
[9] M. Ross, “Relation of Implicit Theories to the Construction of Personal Histories,” Psychological Review, Vol. 96, No. 2, 1989, pp. 341-357. doi:10.1037/0033-295X.96.2.341
[10] A. A. Stone, et al., “Patient Compliance with Paper and Electronic Diaries,” Controlled Clinical Trials, Vol. 24, No. 2, 2003, pp. 182-199. doi:10.1016/S0197-2456(02)00320-3
[11] L. A. Penner, et al., “Individual Differences in Intraperson Variability in Mood,” Journal of Personality and Social Psychology, Vol. 66, No. 4, 1994, pp. 712-721. doi:10.1037/0022-3514.66.4.712
[12] S. Shiffman, A. A. Stone and M. R. Hufford, “Ecological Momentary Assessment,” Annual Review of Clinical Psychology, Vol. 4, 2008, pp. 1-32. doi:10.1146/annurev.clinpsy.3.022806.091415
[13] B. L. Carter, et al., “Real-Time Craving Differences between Black and White Smokers,” The American Journal on Addictions, Vol. 19, No. 2, pp. 136-140.doi:10.1111/j.1521-0391.2009.00020.x
[14] M. D. Litt, R. M. Kadden and E. Kabela-Cormier, “Individualized Assessment and Treatment Program for Alcohol Dependence: Results of an Initial Study to Train Coping Skills,” Addiction, Vol. 104, No. 11, 2009, pp. 1837-1838. doi:10.1111/j.1360-0443.2009.02693.x
[15] S. Shiffman, et al., “First Lapses to Smoking: Within-Subjects Analysis of Real-Time Reports,” Journal of Consulting and Clinical Psychology, Vol. 64, No. 2, 1996, pp. 366-379. doi:10.1037/0022-006X.64.2.366
[16] G. Dunton, et al., “Using Ecological Momentary Assessment to Examine Antecedents and Correlates of Physical Activity Bouts in Adults Age 50+ Years: A Pilot Study,” Annals of Behavioral Medicine, Vol. 38, No. 3, 2009, pp. 249-255. doi:10.1007/s12160-009-9141-4
[17] G. Dunton, et al., “Mapping the Social and Physical Contexts of Physical Activity across Adolescence Using Ecological Momentary Assessment,” Annals of Behavioral Medicine, Vol. 34, No. 2, 2007, pp. 144-153. doi:10.1007/BF02872669
[18] T. W. Kamarck, et al., “Psychosocial Demands and Ambulatory Blood Pressure: A Field Assessment Approach,” Physiology & Behavior, Vol. 77, No. 4-5, 2002, pp. 699-704. doi:10.1016/S0031-9384(02)00921-6
[19] L. Litcher-Kelly, et al., “Feasibility and Utility of an Electronic Diary to Assess Self-Report Symptoms in Patients with Inflammatory Bowel Disease,” Annals of Behavioral Medicine, Vol. 33, No. 2, 2007, pp. 207-212.doi:10.1007/BF02879902
[20] J. M. Smyth, et al., “Daily Psychosocial Factors Predict Levels and Diurnal Cycles of Asthma Symptomatology and Peak Flow,” Journal of Behavioral Medicine, Vol. 22, No. 2, 1999, pp. 179-193. doi:10.1023/A:1018787500151
[21] A. A. Stone, et al., “The Experience of Rheumatoid Arthritis Pain and Fatigue: Examining Momentary Reports and Correlates over One Week,” Arthritis Care & Research, Vol. 10, No. 3, 1997, pp. 185-193. doi:10.1002/art.1790100306
[22] S. L. Curran, A. O. Beacham and M. A. Andrykowski, “Ecological Momentary Assessment of Fatigue Following Breast Cancer Treatment,” Journal of Behavioral Medicine, Vol. 27, No. 5, 2004, pp. 425-444. doi:10.1023/B:JOBM.0000047608.03692.0c
[23] R. Dawes, “The Robust Beauty of Improper Linear Models in Decision Making,” American Psychologist, Vol. 34, No. 7, 1979, pp. 571-582. doi:10.1037/0003-066X.34.7.571
[24] N. K. Aaronson, et al., “The European Organization for Research and Treatment of Cancer QLQ-C30: A Quality-of-Life Instrument for Use in International Clinical Trials in Oncology,” Journal of the National Cancer Institute, Vol. 85, No. 5, 1993, pp. 365-376. doi:10.1093/jnci/85.5.365
[25] M. Groenvold, et al., “Validation of the EORTC QLQ-C30 Quality of Life Questionnaire through Combined Qualitative and Quantitative Assessment of Patient-Observer Agreement,” Journal of Clinical Epidemiology, Vol. 50, No. 4, 1997, pp. 441-450.doi:10.1016/S0895-4356(96)00428-3
[26] J. A. Hanley, et al., “Statistical Analysis of Correlated Data Using Generalized Estimating Equations: An Orienation,” American Journal of Epidemiology, Vol. 157, No. 4, 2003, pp. 364-375. doi:10.1093/aje/kwf215
[27] J. W. Hardin, and J. M. Hilbe, “Generalized Estimating Equations,” Boca Raton, FL: Chapman & Hall/CRC, 2003.
[28] L. Claassens, et al., “Health-Related Quality of Life in Non-Small-Cell Lung Cancer: An Update of a Systematic Review on Methodologic Issues in Randomized Controlled Trials,” Journal of Clinical Oncology, Vol. 29, No. 15, 2011, pp. 2104-2120. doi:10.1200/JCO.2010.32.3683
[29] D. S. Moskowitz, “Ecological Momentary Assessment: What It Is and Why It Is a Method of the Future in Clinical Psychopharmacology,” Journal of psychiatry & Neuroscience, Vol. 31, No. 1, 2006, p. 13.
[30] S. Chaiken, “The Heuristic Model of Persuasion,” In: M. P. Zanna, J. M. Olson and C. P. Herman,Eds., Social Influence: The Ontario Symposium, Vol. 5, Lawrence Erlbaum Associates, Hillsdale, 1987, pp. 3-39.
[31] S. Chaiken, “Heuristic versus Systematic Information Processing and the Use of Source versus Message Cues in Persuasion,” Journal of Personality and Social Psychology, Vol. 39, No. 5, 1980, pp. 752-766.doi:10.1037/0022-3514.39.5.752
[32] B. Schwartz, “The Paradox of Choice,” HarperCollins, New York, 2004.

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