Health and Psychosocial Outcomes in Long-Term Lymphoma Survivors
Survival rates for both non-Hodgkin's (NHL) and Hodgkin's lymphoma (HL) have improved in
recent years due to the development of better treatments. However, the diagnosis and
treatment may leave a cancer survivor with long-term consequences. It is recognized that
patients cured of HL have increased mortality due to long-term effects of treatment. The
literature also suggests that patients cured of NHL suffer from long-term complications.
These complications may include infertility, cardiovascular disease, pulmonary disease,
secondary cancer, osteoporosis, fatigue, and psychological disease. Limitations of the
current literature on lymphoma survivors include that the majority of studies are
retrospective in nature, and therefore do not take into account other risk factors for
development of chronic health conditions, such as tobacco use, exercise, family history, and
specifics of the cancer treatment. In addition, few studies have attempted to explore the
relationship between chronic health conditions, psychological distress, patient-physician
communication, and quality of life (QOL) in lymphoma survivors.
The aims and objectives of this research are to identify chronic health conditions,
psychological disease, QOL, and patient preferences for survivorship care. A prediction
model will then be developed integrating demographic, clinical, and health behavior data
with chronic health conditions to predict poor psychosocial outcomes.
Subjects will be asked to participate in an oral interview with the primary investigator.
The survey consists of demographic information, employment and workplace information, the
Charlson Comorbidity Index, the Qualify of Life-Cancer Survivor questionnaire, the PHQ-9 (a
depression screening tool), the Impact of Events Scale (a post-traumatic stress disorders
screen), the State-Trait Anxiety Index, the Holmes-Rahe Stress Scale, Brief Fatigue
Inventory, Leisure Time, Exercise Questionnaire, as well as questions pertaining to
patient-physician communication and preferences for follow-up care. There are a series of
qualitative or open-ended questions at the end of the survey, designed to understand the
experience of being a survivor of lymphoma. These responses will be audio-taped (with the
consent of the participant) in order to capture the verbatim responses of the participants,
which is necessary for analysis of qualitative data.
Data will be entered into a password-protected database maintained by the primary
investigator. Quantitative analysis will be done in JMP®7 statistical software. Analysis
will be via multiple regression, with quality of life as the primary outcome. Predictive
variables will include demographics, treatment data, comorbidities, fatigue, exercise,
workplace issues, depression, anxiety, and post-traumatic stress disorder. Each variable
will also be analyzed in a univariate model. Qualitative questions will be analyzed
separately using grounded theory, a form of analysis that can be used to generate new ideas.
This will involve selective coding technique, grouping concepts into categories, which lead
to themes between the categories.
There are few risks involved with this study. It is possible that subjects may experience
psychological distress due to the sensitive nature of some of the questions. In this case,
participants may stop the interview at any time and withdraw consent. However, it is
anticipated that this is unlikely to occur. In the event that the investigator finds that a
subject has screened positive for depression, post-traumatic stress disorder, or anxiety;
the patient's primary care physician will be notified, as long as the patient gives consent.
If the patient is found to be suicidal at the time of the interview, the interviewer will
accompany the patient to the emergency room.
Benefits of this research are the improved understanding of long-term outcomes in lymphoma
survivors and the identification of factors that predict for poor QOL, so that in the
future, interventions can be made to improve QOL in this patient population.
Observational Model: Cohort, Time Perspective: Cross-Sectional
Quality of life
cross-sectional (time of interview)
Carrie A Thompson, M.D.
Weill Medical College of Cornell University
United States: Institutional Review Board
|Weill Cornell Medical College||New York, New York 10021|