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| Name | Class |
|---|---|
| Cancer Research UK | OTHER |
| National Institute for Health Research, United Kingdom | OTHER_GOV |
| Royal Marsden NHS Foundation Trust | OTHER |
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Theranostics is the use of a diagnostic test to decide which patients will benefit from a certain treatment.
The current standard treatment for patients with myeloma is induction chemotherapy followed by peripheral stem cell transplant. Although there are options for timing of treatments, patient outcomes are variable and the investigators do not currently know which patients benefit from which treatment schedule. There is evidence to suggest that residual disease on imaging after treatment is an indicator for a worse prognosis, however the best time point for this imaging is currently not known. This study is designed to show if there is an optimum time point for correlation between imaging and prognosis.
Several studies have indicated that MRI is better at detecting disease than FDG PET/CT and the investigators will confirm this when patients are first diagnosed, by performing both FDG PET/CT and whole body diffusion weighted MRI.
Patients will then be followed up with whole body diffusion weighted MRI after induction chemotherapy and 3 months post autograft. The investigators will look at the amount of disease present on these scans and correlate this with outcomes.
There are likely to be other factors which influence patient outcomes (such as genetics) and the investigators will also look at some of these. Patients who undergo autograft have regular blood tests and marrow samples taken as part of routine care, the investigators will use some of these samples (without compromising the patients treatment) to analyses some of these other factors. If the investigators are able to determine a correlation of genetic factors with outcome this information could be used in future research.
Theranostics is the use of a diagnostic test to decide which patients will benefit from a certain treatment.
The current standard treatment for patients with myeloma is induction chemotherapy followed by peripheral stem cell transplant. Although there are options for timing of treatments, patient outcomes are variable and the investigators do not currently know which patients benefit from which treatment schedule. There is evidence to suggest that residual disease on imaging after treatment is an indicator for a worse prognosis, however the best time point for this imaging is currently not known. This study is designed to show if there is an optimum time point for correlation between imaging and prognosis.
Several studies have indicated that MRI is better at detecting disease than FDG PET/CT and the investigators will confirm this when patients are first diagnosed, by performing both FDG PET/CT and whole body diffusion weighted MRI.
Patients will then be followed up with whole body diffusion weighted MRI after induction chemotherapy and 3 months post autograft. The investigators will look at the amount of disease present on these scans and correlate this with outcomes.
There are likely to be other factors which influence patient outcomes (such as genetics) and the investigators will also look at some of these. Patients who undergo autograft have regular blood tests and marrow samples taken as part of routine care, the investigators will use some of these samples (without compromising the patients treatment) to analyses some of these other factors. If the investigators are able to determine a correlation of genetic factors with outcome this information could be used in future research.
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| Measure | Description | Time Frame |
|---|---|---|
| Construct a ROC curve and calculate area under the curve (AUC) to show that the burden of disease at 3 months post autograft (WB-DWI score) is predictive of disease status at 2 years. | 2 years post autograph |
| Measure | Description | Time Frame |
|---|---|---|
| Use multivariate/univariate analysis to identify the best single or combination MRI parameter(s) to predict disease status at 2 years | 2 years post autograph | |
| Identify optimal cut-off point with best sensitivity and specificity to predict disease status at 2 years. |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with myeloma planned for autograft.
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| Name | Affiliation | Role |
|---|---|---|
| Christina Messiou, Dr | Royal Marsden NHS Foundation Trust | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Royal Marsden NHS Foundation Trust | Sutton | Surrey | SM2 5PT | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 42418394 | Derived | Basty N, Kaiser MF, Pawlyn C, Boyd KD, Smith K, Thomas K, Porta N, Meo D, Emsley R, Winfield J, Dragan A, Doran S, Koh DM, Whitcher B, Messiou C. AI derived Whole-Body MRI metrics in multiple myeloma patients reveal unique insights into body composition and outcomes. Blood Adv. 2026 Jul 8:bloodadvances.2026020852. doi: 10.1182/bloodadvances.2026020852. Online ahead of print. | |
| 34559006 |
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| ID | Term |
|---|---|
| D009369 | Neoplasms |
| D054219 | Neoplasms, Plasma Cell |
| ID | Term |
|---|---|
| D009370 | Neoplasms by Histologic Type |
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Patients who undergo autograft have regular blood tests and marrow sampling and we will use these samples, to look at other factors which influence patient outcomes such as genetics, without compromising routine care. Some of the genetic tests performed on the bone marrow are not routine so we will obtain additional consent to do this.
| 2 years post autograph |
| Calculate PFS for patients grouped by optimal cut-off. | 2 years post autograph |
| Overall survival (OS) in patients with residual disease on WB-DWI post induction and 3 months post autograft. | 2 years post autograph |
| Derived |
| Messiou C, Porta N, Sharma B, Levine D, Koh DM, Boyd K, Pawlyn C, Riddell A, Downey K, Croft J, Morgan V, Stern S, Cheung B, Kyriakou C, Kaczmarek P, Winfield J, Blackledge M, Oyen WJG, Kaiser MF. Prospective Evaluation of Whole-Body MRI versus FDG PET/CT for Lesion Detection in Participants with Myeloma. Radiol Imaging Cancer. 2021 Sep;3(5):e210048. doi: 10.1148/rycan.2021210048. |