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| ID | Type | Description | Link |
|---|---|---|---|
| NCI-2020-01239 | Registry Identifier | CTRP (Clinical Trial Reporting Program) |
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This trial evaluates the risk of chemotherapy toxicity in older patients with blood cancer or non-small cell lung cancer. The purpose of this study is to describe a patient's wellness before and after chemotherapy treatment. This may help researchers better understand patient's ability to tolerate treatment and in the future devise the best treatment for a patient based on their "fitness."
PRIMARY OBJECTIVE:
I. To validate the accuracy and predictive ability of the Cancer and Aging Research Group (CARG) Chemo-Toxicity calculator in untreated patients with hematologic malignancy and non-small cell lung cancer, as well as relapsed patients with a hematologic malignancy intended to begin chimeric antigen receptor (CAR) T cell therapy.
Ia. Determine if the CARG Chemo-Toxicity calculator predicts grade 3-5 toxicity in older adult patients with hematologic malignancy undergoing treatment.
Ib. Determine if CARG Geriatric Assessment (GA) metrics predict grade 3-5 toxicity in older adults with hematologic malignancy undergoing treatment.
Ic. Identify the association between frailty metrics and relative dose intensity in older adults with hematologic malignancy.
Id. To evaluate feasibility of CARG GA and functional assessment implementation in older adults with non-small cell lung cancer (NSCLC).
SECONDARY OBJECTIVES:
I. To determine the relationship of frailty metrics (CARG chemo-toxicity calculator and geriatric assessment metrics) with health related quality of life (HRQL) over time.
II. To identify the relationship of frailty metrics (chemo-toxicity calculator and GA metrics) with physical function as measured by the short physical performance battery (SPPB).
III. To determine the association of molecular markers of aging (OSU_Senescence, Hovarth epigenetic clock/deoxyribonucleic acid [DNA]ge, inflammatory cytokines, changes in peripheral blood T lymphocyte subsets) with risk of chemotherapy toxicity using the Chemo-Toxicity calculator and other prognostic factors (e.g. age, disease, stage, body composition by imaging).
IV. In the NSCLC cohort we will determine the association between treatment efficacy and toxicity with changes in the stool microbiome.
OUTLINE:
Patients complete questionnaires over 30-40 minutes about daily activity and feelings, complete thinking and walking tests over 10 minutes, and undergo collection of blood samples before the first dose of chemotherapy and 90, 180, and 365 days after first dose of chemotherapy. Patients with non-small lung cancer also undergo collection of stool sample.
After completion of study treatment, patients are followed up every 6 months.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Observational (questionnaire, assessment, biospecimen) | Patients complete questionnaires over 30-40 minutes about daily activity and feelings, complete thinking and walking tests over 10 minutes, and undergo collection of blood samples before the first dose of chemotherapy and 90, 180, and 365 days after first dose of chemotherapy. Patients with non-small lung cancer also undergo collection of stool sample. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Biospecimen Collection | Procedure | Undergo collection of blood and stool samples |
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| Measure | Description | Time Frame |
|---|---|---|
| Prognostic ability of the CARG chemotoxicity calculator in patients newly diagnosed with hematologic malignancy | 365 days after first dose of chemotherapy | |
| Predictive ability of the Cancer and Aging Research Group (CARG) Chemo-Toxicity calculator | 365 days after first dose of chemotherapy | |
| Predictive ability of Chemo-Toxicity calculator to predict grade 3-5 toxicity | Will fit a Cox regression model for time to toxicity (grades 3-5) containing the baseline chemo-toxicity risk score as the only predictor. The overall ability of the model to distinguish grade 3-5 from grade 1-2 toxicity will be evaluated using Harrell's C-statistic, which can be viewed as a generalization of the area under the curve measurement for receiver operator characteristics (ROC's) curves based on binary outcome data. A 95% confidence interval will be constructed for the C-statistic and if the lower bound is greater than 0.5 (expected value if the risk score is not predictive of toxicity) we will conclude that risk score is significantly able to distinguish between toxicity grades. | 365 days after first dose of chemotherapy |
| Predictive ability of Geriatric Assessment (GA) metrics to predict grade 3-5 toxicity | Will fit a Cox regression model for time to toxicity (grades 3-5) containing the baseline chemo-toxicity risk score as the only predictor. The overall ability of the model to distinguish grade 3-5 from grade 1-2 toxicity will be evaluated using Harrell's C-statistic, which can be viewed as a generalization of the area under the curve measurement for ROC's curves based on binary outcome data. A 95% confidence interval will be constructed for the C-statistic and if the lower bound is greater than 0.5 (expected value if the risk score is not predictive of toxicity) we will conclude that risk score is significantly able to distinguish between toxicity grades. | 365 days after first dose of chemotherapy |
| Association between frailty metrics and relative dose intensity (RDI) |
| Measure | Description | Time Frame |
|---|---|---|
| Relationship of frailty metrics with health related quality of life over time | Linear mixed models will be used in the analyses. Each model will include effects of each prognostic variable of interest, time (baseline vs. end of treatment), and time-by-prognostic variable interactions to determine if the associations between the prognostic variables and the outcome differs at baseline and end of treatment. An unstructured covariance matrix will be used to model the relationship between outcome measurements from the same patient. |
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Inclusion Criteria:
Exclusion Criteria:
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Patients diagnosed with a hematologic malignancy and are either untreated or relapsed and newly diagnosed with NSCLC who intend to receive treatment at the Ohio State University
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| Name | Affiliation | Role |
|---|---|---|
| Ashley E Rosko, MD | Ohio State University Comprehensive Cancer Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ohio State University Comprehensive Cancer Center | Columbus | Ohio | 43210 | United States |
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| Label | URL |
|---|---|
| Jamesline | View source |
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| Cognitive Assessment | Procedure | Complete thinking test |
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| Physical Performance Testing | Other | Complete walking test |
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| Quality-of-Life Assessment | Other | Ancillary studies |
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| Questionnaire Administration | Other | Complete questionnaire |
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Will explore the relationship of RDI and MAX2 (reduced and prescribed) with clinical and biologic factors of frailty. RDI (>= 85% versus [vs.] < 85%) will be treated as a continuous and dichotomous variable. The distribution of RDI and MAX2 will be examined graphically and transformed to normality as appropriate. Linear regression for continuous RDI and logistic regression for dichotomized RDI will be used to understand the relationship with RDI and independent variables (e.g. GA scores, age, short physical performance battery [SPPB] etc.) Stepwise regression will be used to identify significant clinical and biologic factors (e.g. OSU_Senescence) that are independently associated with continuous or dichotomized RDI. |
| 365 days after first dose of chemotherapy |
| 365 days after first dose of chemotherapy |
| Relationship of frailty metrics with physical function | Linear mixed models will be used in the analyses. Each model will include effects of each prognostic variable of interest, time (baseline vs. end of treatment), and time-by-prognostic variable interactions to determine if the associations between the prognostic variables and the outcome differs at baseline and end of treatment. An unstructured covariance matrix will be used to model the relationship between outcome measurements from the same patient. | 365 days after first dose of chemotherapy |
| Molecular markers of aging with risk of chemotherapy toxicity using the Chemo-Toxicity calculator | Will determine the association of molecular markers of aging with risk of chemotherapy toxicity using the Chemo-Toxicity calculator and other prognostic factors (e.g. age, disease, stage, body composition by imaging). Linear mixed models will be used in the analyses. Each model will include effects of each prognostic variable of interest, time (baseline vs. end of treatment), and time-by-prognostic variable interactions to determine if the associations between the prognostic variables and the outcome differs at baseline and end of treatment. An unstructured covariance matrix will be used to model the relationship between outcome measurements from the same patient. | 365 days after first dose of chemotherapy |
| ID | Term |
|---|---|
| D019337 | Hematologic Neoplasms |
| D002289 | Carcinoma, Non-Small-Cell Lung |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D006402 | Hematologic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
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| ID | Term |
|---|---|
| D000073216 | Mental Status and Dementia Tests |
| D005080 | Exercise Test |
| ID | Term |
|---|---|
| D009483 | Neuropsychological Tests |
| D011581 | Psychological Tests |
| D004191 | Behavioral Disciplines and Activities |
| D006334 | Heart Function Tests |
| D003935 | Diagnostic Techniques, Cardiovascular |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D012129 | Respiratory Function Tests |
| D003948 | Diagnostic Techniques, Respiratory System |
| D016552 | Ergometry |
| D008919 | Investigative Techniques |
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