Clinical trial NCT04364724: CTFEA Myeloma Study
Official title: Prospective Application of CTFEA for Monitoring Disease Progression in Active Multiple Myeloma
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Myeloma Multiple
Metastatic Bone Tumor
Keywords: CT-based finite element analysis
Pathologic fracture
Multiple myeloma
Disease progression
Monitoring
Response to treatment
Lead sponsor: Tel-Aviv Sourasky Medical Center
Sponsor class: OTHER_GOV
Collaborators: name: Tel Aviv University
First posted: 2020-04-28
Enrollment: 200
Sex: ALL
Minimum age (years): 18
Maximum age (years): 95
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with Active Multiple Myeloma

Brief summary: Patients with Multiple Myeloma are monitored for disease progression and for response to treatment by the treating hematologist or oncologist. Laboratory tests are usually utilized for these purposes. The role of imaging is confined to follow-up the progression of visible bone lesions. We suggest that microscopic bone lesions impair bone structure well before they grow enough to be visible on a CT scan. This impairment of bone strength can probably be captured by application of CT-based finite element analysis to the CT scans that were performed for monitoring of progression of the disease.

Detailed description: Background

Multiple myeloma (MM) is the most common primary bone malignancy, caused by proliferation of plasma cells secreting immunoglobulins. Active MM (aMM) is characterized in many patients by multiple lytic bone lesions, presenting with pain in the involved bones (e.g. pelvis, spine, etc.). In a recent publication, key-opinion leaders of multiple-myeloma state "MM-induced bone disease is a hallmark of MM; up to 80% of patients present with osteolytic bone lesions at diagnosis and have an increased risk of skeletal-related events (SREs) associated with increased morbidity and mortality" (Terpos et al, 2018). Approximately 60% of myeloma patients will develop a fracture during the disease course" (Terpos et al, 2018). Current CT scans provide qualitative measures of bone involvement detected only after irreversible damage has occurred and which cannot predict disease evolution so to optimize treatment and enhance life quality and longevity.

Medical treatment modalities, including multi-agent chemotherapy and bone marrow transplantation, may stop progression of MM, and prevent further bone lesions. Myeloma response to therapy is usually monitored by measurement of the monocloncal protein which is secreted by the malignant plasma cells into the blood and urine. This protein includes an intact immunoglobulin - M-SPIKE - which is measured by serum protein electrophoresis (SPEP) and, Circulating free light chains - kappa and lambda. Usually one of the chains is "involved" in the disease; The level of M-SPIKE and the ratio of the "involved" to "uninvolved" chains is used to monitor disease progression. The role of imaging technologies in monitoring progression of the disease is less defined. Low-dose total body CT scans are recommended as second-line imaging (total body MRI is first-line) during the initial diagnostic workup of MM by the most current guidelines of National Institute for Healthcare Excellence (NICE, 2016). The guidelines encourage further research of the role of various imaging modalities in treatment of MM:

"Newer imaging techniques are replacing skeletal surveys for assessing myeloma related bone disease in people with newly diagnosed myeloma. However, the most effective tech-nique is not known. Outcomes of interest are lesion detection, sensitivity and specificity for myeloma related bone disease, patient acceptability, incremental upstaging, radiation exposure, risk of second primary cancer, the impact of additional information on predicting progression-free survival, overall survival and skeletal related events." (NICE, 2016) As previously stated, current imaging modalities visualize bone lesions but do not quantify their progression, any response to therapy or their impact on bone strength. A novel scientific tool that describes bone's response by mathematical equations and is based on CT scans of MM patients, allows to construct a 3-D model of patient's femurs and vertebrae including the inhomogeneous material properties, virtually loads the bones by physiological loads associated with patient's weight and determine the deformations and strains by a computer simulation. This technology, termed CTFEA, allows a quantitative evaluation of bone's strength and risk of fracture, was double-blinded validated ex-vivo, and clinically validated in a retrospective clinical trial on a cohort of 50 patients with metastatic tumors to their femurs (Sternheim et al, 2018).

Combining the engineering and scientific expertise with the clinical knowledge and database of MM patients accumulated during the past ten years, may identify by monitoring femurs' and vertebrae' strength the evolution of MM, and trigger the need of prophylactic surgeries. Such CTFEA has the potential to revolutionize MM treatment by providing the MDs quantitative scientific measures to monitor and change treatment options so to optimize medication prescription and enhance life-quality and longevity of MM patients on one hand, and determine with high level of accuracy the risk of impending fracture due to metastatic tumors to the femurs and vertebrae.

Preliminary results on a cohort of seven MM patients (Cohen et al, 2017), has recently been presented in Dec 2017 at the ASH conference in the USA. These results showed the potential of assisting MDs to determine disease evolution and treatment. Since the vertebrae are prone to MM involvement, we plan to validate the CTFEA methods for such vertebrae with MM involvement by comparing experiments performed on cadaveric human vertebrae with the computational simulation. In addition, we propose to in-vivo validate the accuracy and predictability of patient specific CTFEA of vertebrae and femurs by a clinical trial on a cohort of MM patients treated at Sourasky medical center.

Rationale CTFEA may add efficacy to CT scans used for follow-up of disease progression. This analysis can detect differences of as little as 10% in bone strength. It has the ability to detect changes even in normal looking bone on CT and not just in lytic lesions. In addition, CTFEA characterises the effect of each myeloma lesion on bone structure and calculates the risk of a pathologic fracture.

Study hypothesis:

We hypothesize that CTFEA analysis of LDTBCT will detect changes over time in patients with a dynamic disease, even when these changes in CT are undetectable to the human eye.

Study objectives:

Primary objective:

To observe CTFEA-determined bone strength changes over time in patients with Active MM.

Secondary objectives

1. To measure CTFEA changes over a period of 12 months in lumbar vertebrae and femurs of patients with AMM.
2. To determine correlation between CTFEA and clinical indicators of response to treatment (e.g. light chains, clinical staging of bone lesions).
3. To compare CTFEA changes over time between patients responding to AMM treatment and those who do not respond to treatment.

Methods Study design This is a prospective study with one patient group. All patients will undergo three Low-Dose Total Body CT (LDTBCT) scans as part of diagnostic workup for MM, which represents our current common practice: at 0, 6 and 12 months into treatment (or 3 CT scans at least 6 months apart).

All three scans will be sent for CTFEA, which is not part of the common practice. The CTFEA results will be compared to clinical assessments as per patient files and light chain values on blood work. Changes in lesion size will be compared to changes that the lesion inflicts in bone structure and changes in the risk of fracture.

Bone strength in both femurs and lower lumbar vertebra will be analyzed even where there are no lytic lesions for changes in bone strength.

Results will be correlated with Myeloma clinical variables including baseline demographic and disease charateristics, therapy details and response to treatment over time.

Patients will continue followup, for recording of skeletal related events (fratures or new lytic lesions)

Measured parameters

1. Primary and secondary disease diagnoses and their ICD-9 codes.
2. Patient ambulatory status at time of MM diagnosis: independent walker; cane ambulator; walker ambulator; wheel chair bound.
3. Time since patient was independent walker, ECOG performance status (Oken et al, 1982)(Appendix A).
4. Treatment for osteoporosis and duration.
5. Date of diagnosis of active MM (and preceding plasma cell dyscrasia if relevant)
6. Myeloma treatment details (dose \& dates) and response to therapy according to IMWG criteria (IMWG, 2010)(Appendix B)
7. CT scans (used for CTFEA) dates.
8. Last patient follow-up date.

10) Medical center at which the patient received their oncology treatment before the hematology referral.

11) Laboratory results, specifically: Myeloma paraprotein measures including SPEP, quantitative immunoglobulins and free light chain values; kidney function; CBC; LDH; B2MG; FISH cytogenetics; BM PC% at diagnosis 12) active myeloma clinical presentation: CRAB criteria (hypercalcemia / renal / anemia / bone lesions); and or SLIM-CRAB criteria (FLC ratio\>100; focal lesions on MRI or PETCT; BM PC\>60%); 13) clinical status at time of CT scan (newly diagnosed MM (NDMM); relapsed refractory MM \[RRMM\]) 14) VAS (Visual Analogue Scale) for pain and Harris Hip Score

Eligibility criteria: Inclusion Criteria:

* All patients with Active Multiple Myeloma

Exclusion Criteria:

* Inability to provide informed consent or lack of consent.
* Inadequate CT scans

Primary outcomes:
measure: Change in bone strength
timeFrame: 12 months
measure: Quantification of bone strength
timeFrame: 12 months
Secondary outcomes:
measure: Pathological fracture
timeFrame: 12 months of follow up
measure: Mortality
timeFrame: 12 months
measure: Loss of ambulatory ability
timeFrame: 12 months
Other outcomes:
Locations:
Study officials:
References:
citation: Myeloma: diagnosis and management. London: National Institute for Health and Care Excellence (NICE); 2018 Oct. Available from http://www.ncbi.nlm.nih.gov/books/NBK553585/
citation: Sternheim A, Giladi O, Gortzak Y, Drexler M, Salai M, Trabelsi N, Milgrom C, Yosibash Z. Pathological fracture risk assessment in patients with femoral metastases using CT-based finite element methods. A retrospective clinical study. Bone. 2018 May;110:215-220. doi: 10.1016/j.bone.2018.02.011. Epub 2018 Feb 20.
citation: Terpos E, Ntanasis-Stathopoulos I, Gavriatopoulou M, Dimopoulos MA. Pathogenesis of bone disease in multiple myeloma: from bench to bedside. Blood Cancer J. 2018 Jan 12;8(1):7. doi: 10.1038/s41408-017-0037-4.
citation: Oken MM, Creech RH, Tormey DC, Horton J, Davis TE, McFadden ET, Carbone PP. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982 Dec;5(6):649-55. No abstract available.