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| ID | Type | Description | Link |
|---|---|---|---|
| NCI-2021-05723 | Registry Identifier | CTRP (Clinical Trial Reporting Program) | |
| 0S-20-10 | Other Identifier | USC / Norris Comprehensive Cancer Center | |
| P30CA014089 | U.S. NIH Grant/Contract | View source | |
| R37CA256867 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Cancer Institute (NCI) | NIH |
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This study assesses how personal relationships (such as friendships, family relationships, or romantic partners) influence the physical activity (exercise) and well-being of young adult cancer survivors. Researchers also hope to learn how social relationships change after a cancer diagnosis, and how these changes might impact important health behaviors. The information provided may help researchers learn more about better ways to support young cancer patients in the future through interventions that help maintain good social relationships and health levels of physical activity.
PRIMARY OBJECTIVES:
I. Characterize the trajectories of social health in young adult (YA) cancer patients.
II. Investigate the longitudinal associations between social health and activity behaviors in YA cancer patients.
III. Explore the effects of sociodemographic and clinical characteristics on the relationship between social health, activity behaviors, and quality of life.
OUTLINE:
Patients complete surveys over 40 minutes and wear an actigraph GT3X-BT accelerometer continuously for 7 days at baseline, 3, 6, and 12 months.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Observational (actigraph, surveys) | Patients complete surveys and wear an actigraph GT3X-BT accelerometer continuously for 7 days at baseline, 3, 6, and 12 months. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Medical Device Usage and Evaluation | Other | Wear an actigraph GT3X-BT accelerometer |
|
| Measure | Description | Time Frame |
|---|---|---|
| Rate of Change in trajectories of social health | Social health variables include the number, frequency and duration of hospitalizations, specifics of cancer diagnosis (i.e., stage at diagnosis, pertinent histology, recurrence or progression of disease), chemotherapy type, surgery related to cancer diagnosis, radiation field, immunotherapy type, and other relevant therapies related to cancer treatment. Changes in above variables will be measured using latent growth curve models to measure latent intercept (initial level), and the latent slope (rate of change) of social health variables during the course of therapy. | Baseline up to 1 year |
| Rate of Change in trajectories of physical activity | Changes will be measured using latent growth curve models to measure latent intercept (initial level) and the latent slope (rate of change) of physical activity during the course of therapy. | Baseline up to 1 year |
| Rate of Change in trajectories of quality of life | Changes will be measured using latent growth curve models to measure latent intercept (initial level) and the latent slope (rate of change) of quality of life during the course of therapy. | Baseline up to 1 year |
| Moderation by gender | Will conduct multi-group analyses by the categories of study moderators (e.g., gender, race/ethnicity, socioeconomic status [SES], health status). The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit. The log-likelihood values with (versus [vs.] without) the equality constraints on the group-specific pathways to determine if the strength of associations estimated in the models significantly differ by the groups of each moderator (e.g., gender: female vs. male). | Up to 1 year |
| Moderation effect of race/ethnicity |
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Inclusion Criteria:
Exclusion Criteria:
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Patients diagnosed and/or treated with cancer between ages 18-39 at University of Southern California (USC) hospitals.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Kimberly A Miller, PhD | Contact | 323-865-0674 | kim.miller@med.usc.edu |
| Name | Affiliation | Role |
|---|---|---|
| Kimberly Miller, PhD | University of Southern California | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Los Angeles General Medical Center | Recruiting | Los Angeles | California | 90033 | United States |
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| Quality-of-Life Assessment | Other | Complete survey |
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| Survey Administration | Other | Complete survey |
|
Moderation effect is analyzed by the interaction between the independent variable (X), and the moderator variable (Y) in a regression model, where the endpoint is the dependent variable (Z). Moderation effect is the endpoint itself, indicated by the significance of the interaction term's regression coefficient (B3), which shows how the relationship between X and Y changes depending on the level of Z. 'X' is social health, physical activity, and quality of life. 'Y' is race/ethnicity. 'Z' is moderation effect. The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit. |
| Up to 1 year |
| Moderation effect of Socio-Economic Status (SES) | Moderation effect is analyzed by the interaction between the independent variable (X), and the moderator variable (Y) in a regression model, where the endpoint is the dependent variable (Z). Moderation effect is the endpoint itself, indicated by the significance of the interaction term's regression coefficient (B3), which shows how the relationship between X and Y changes depending on the level of Z. 'X' is social health, physical activity, and quality of life. 'Y' is socio-economic status. 'Z' is moderation effect. The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit. | Up to 1 year |
| Moderation effect of health status | Moderation effect is analyzed by the interaction between the independent variable (X), and the moderator variable (Y) in a regression model, where the endpoint is the dependent variable (Z). Moderation effect is the endpoint itself, indicated by the significance of the interaction term's regression coefficient (B3), which shows how the relationship between X and Y changes depending on the level of Z. 'X' is social health, physical activity, and quality of life. 'Y' is health status. 'Z' is moderation effect. The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit. | Up to 1 year |
| USC / Norris Comprehensive Cancer Center | Recruiting | Los Angeles | California | 90033 | United States |
|
| ID | Term |
|---|---|
| D016543 | Central Nervous System Neoplasms |
| D006689 | Hodgkin Disease |
| D001859 | Bone Neoplasms |
| D001932 | Brain Neoplasms |
| D013736 | Testicular Neoplasms |
| D008228 | Lymphoma, Non-Hodgkin |
| D002583 | Uterine Cervical Neoplasms |
| D015179 | Colorectal Neoplasms |
| D010051 | Ovarian Neoplasms |
| D018276 | Carcinoma, Medullary |
| ID | Term |
|---|---|
| D009423 | Nervous System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D009422 | Nervous System Diseases |
| D008223 | Lymphoma |
| D009370 | Neoplasms by Histologic Type |
| D008232 | Lymphoproliferative Disorders |
| D008206 | Lymphatic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
| D007160 | Immunoproliferative Disorders |
| D007154 | Immune System Diseases |
| D001847 | Bone Diseases |
| D009140 | Musculoskeletal Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D004701 | Endocrine Gland Neoplasms |
| D005834 | Genital Neoplasms, Male |
| D014565 | Urogenital Neoplasms |
| D005832 | Genital Diseases, Male |
| D000091662 | Genital Diseases |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
| D004700 | Endocrine System Diseases |
| D013733 | Testicular Diseases |
| D006058 | Gonadal Disorders |
| D014594 | Uterine Neoplasms |
| D005833 | Genital Neoplasms, Female |
| D002577 | Uterine Cervical Diseases |
| D014591 | Uterine Diseases |
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |
| D010049 | Ovarian Diseases |
| D000291 | Adnexal Diseases |
| D018278 | Carcinoma, Neuroendocrine |
| D018358 | Neuroendocrine Tumors |
| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D000230 | Adenocarcinoma |
| D002277 | Carcinoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D018299 | Neoplasms, Ductal, Lobular, and Medullary |
| D009380 | Neoplasms, Nerve Tissue |
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