Breast Screening Clinical Trial
Official title:
Tomosynthesis Mammographic Imaging Screening Trial (TMIST)
Verified date | June 2023 |
Source | Eastern Cooperative Oncology Group |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
This randomized phase III trial studies digital tomosynthesis mammography and digital mammography in screening patients for breast cancer. Screening for breast cancer with tomosynthesis mammography may be superior to digital mammography for breast cancer screening and may help reduce the need for additional imaging or treatment.
Status | Recruiting |
Enrollment | 128905 |
Est. completion date | December 31, 2030 |
Est. primary completion date | December 31, 2030 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Female |
Age group | 45 Years to 74 Years |
Eligibility | Inclusion Criteria: - Women of childbearing potential must not be known to be pregnant or lactating - Patients must be scheduled for, or have intent to schedule, a screening mammogram - Patients must be able to tolerate digital breast tomosynthesis and full-field digital mammographic imaging required by protocol. - Patients must be willing and able to provide a written informed consent - Patients must not have symptoms or signs of benign or malignant breast disease (eg, nipple discharge, breast lump) warranting a diagnostic rather than a screening mammogram, and/or other imaging studies (eg, sonogram); patients with breast pain are eligible as long as other criteria are met - Patients must not have had a screening mammogram within the last 11 months prior to date of randomization - Patients must not have previous personal history of breast cancer including ductal carcinoma in situ - Patients must not have breast enhancements (e.g., implants or injections) - ANNUAL SCREENING REGIMEN ELIGIBILITY CHECK - To be eligible for inclusion in the annual screening regimen one of the following three conditions must be met in addition to the eligibility criteria above: - Patients are pre-menopausal; OR - Post-menopausal aged 45-69 with any of the following three risks factors: - Dense breasts (BIRADS density categories c-heterogeneously dense or d-extremely dense), or - Family history of breast cancer (first degree relative with breast cancer), or, positive genetic testing for any deleterious genes that indicate an increased risk for breast cancer, or - Currently on hormone therapy; OR - Post-menopausal ages 70-74 with either of the following two risk factors: - Dense breasts (BIRADS density categories c-heterogeneously dense or d-extremely dense), or - Currently on hormone therapy - Postmenopausal women are defined as those with their last menstrual period more than 12 months prior to study entry; for the purpose of defining menopausal status for women who have had surgical cessation of their periods, women who no longer have menses due to hysterectomy and oophorectomy will be considered postmenopausal; women who no longer have menses due to hysterectomy without oophorectomy will be considered premenopausal until age 52 and postmenopausal thereafter - All other postmenopausal women are eligible for inclusion in the biennial screening regimen - For those women who cannot be assigned to annual or biennial screening at the time of study entry and randomization because they are postmenopausal, have no family history or known deleterious breast cancer mutation, are not on hormone therapy AND have not had a prior mammogram, breast density will be determined by the radiologist?s recording of it at the time of interpretation of the first study screening examination, either DM or TM; for those who are randomized to TM, radiologists will assign BI-RADS density through review of the DM or synthetic DM portion of the TM examination; such women cannot be part of the planned stratification by screening frequency and are expected to represent far less than 1% of the Tomosynthesis Mammographic Imaging Screening Trial (TMIST) population - Breast density will be determined by prior mammography reports, when available; all other risk factors used to determine patient eligibility for annual or biennial screening will be determined by subject self-report |
Country | Name | City | State |
---|---|---|---|
Argentina | CERIM | Buenos Aires | |
Canada | Saint Joseph's Health Centre | London | Ontario |
Canada | Hopital Du Sacre-Coeur de Montreal | Montreal | Quebec |
Canada | Ottawa Hospital and Cancer Center-General Campus | Ottawa | Ontario |
Canada | CHU de Quebec-Hopital du Saint-Sacrement (HSS) | Quebec City | Quebec |
Canada | Mount Sinai Hospital | Toronto | Ontario |
Canada | Odette Cancer Centre- Sunnybrook Health Sciences Centre | Toronto | Ontario |
Canada | BCCA-Vancouver Cancer Centre | Vancouver | British Columbia |
Korea, Republic of | National Cancer Center-Korea | Goyang-si | Gyeonggi-do |
Puerto Rico | San Juan City Hospital | San Juan | |
United States | University of New Mexico Cancer Center | Albuquerque | New Mexico |
United States | Saint Joseph Mercy Hospital | Ann Arbor | Michigan |
United States | University of Michigan Comprehensive Cancer Center | Ann Arbor | Michigan |
United States | ThedaCare Regional Cancer Center | Appleton | Wisconsin |
United States | Northside Hospital | Atlanta | Georgia |
United States | University of Colorado Hospital | Aurora | Colorado |
United States | Kern Radiology Medical Group Inc | Bakersfield | California |
United States | Mary Bird Perkins Cancer Center | Baton Rouge | Louisiana |
United States | Woman's Hospital | Baton Rouge | Louisiana |
United States | Bronson Battle Creek | Battle Creek | Michigan |
United States | University of Alabama at Birmingham Cancer Center | Birmingham | Alabama |
United States | Sanford Bismarck Medical Center | Bismarck | North Dakota |
United States | Saint Alphonsus Cancer Care Center-Boise | Boise | Idaho |
United States | Saint Luke's Cancer Institute - Boise | Boise | Idaho |
United States | Boston Medical Center | Boston | Massachusetts |
United States | Northeast Georgia Medical Center Braselton | Braselton | Georgia |
United States | Montefiore Medical Center-Einstein Campus | Bronx | New York |
United States | Montefiore Medical Center-Weiler Hospital | Bronx | New York |
United States | Aultman Health Foundation | Canton | Ohio |
United States | Carson Tahoe Regional Medical Center | Carson City | Nevada |
United States | UNC Lineberger Comprehensive Cancer Center | Chapel Hill | North Carolina |
United States | Medical University of South Carolina | Charleston | South Carolina |
United States | University of Virginia Cancer Center | Charlottesville | Virginia |
United States | John H Stroger Jr Hospital of Cook County | Chicago | Illinois |
United States | University of Cincinnati Cancer Center-UC Medical Center | Cincinnati | Ohio |
United States | Cleveland Clinic Foundation | Cleveland | Ohio |
United States | Penrose-Saint Francis Healthcare | Colorado Springs | Colorado |
United States | Prisma Health Richland Hospital | Columbia | South Carolina |
United States | Ohio State University Comprehensive Cancer Center | Columbus | Ohio |
United States | UT Southwestern/Simmons Cancer Center-Dallas | Dallas | Texas |
United States | Carle on Fairchild | Danville | Illinois |
United States | Decatur Memorial Hospital | Decatur | Illinois |
United States | The Women's Imaging Center | Denver | Colorado |
United States | Mercy Medical Center - Des Moines | Des Moines | Iowa |
United States | Henry Ford Hospital | Detroit | Michigan |
United States | Wayne State University/Karmanos Cancer Institute | Detroit | Michigan |
United States | Essentia Health Cancer Center | Duluth | Minnesota |
United States | Duke University Medical Center | Durham | North Carolina |
United States | Easton Hospital | Easton | Pennsylvania |
United States | Arnot Ogden Medical Center/Falck Cancer Center | Elmira | New York |
United States | Radiology Imaging Associates | Englewood | Colorado |
United States | Southpointe-Sanford Medical Center Fargo | Fargo | North Dakota |
United States | Weisberg Cancer Treatment Center | Farmington Hills | Michigan |
United States | Hunterdon Medical Center | Flemington | New Jersey |
United States | Spectrum Health at Butterworth Campus | Grand Rapids | Michigan |
United States | Prisma Health Greenville Memorial Hospital | Greenville | South Carolina |
United States | Penn State Milton S Hershey Medical Center | Hershey | Pennsylvania |
United States | UCHealth Highlands Ranch Hospital | Highlands Ranch | Colorado |
United States | University of North Carolina-Hillsborough Campus | Hillsborough | North Carolina |
United States | Queen's Medical Center | Honolulu | Hawaii |
United States | Carle Hoopeston Regional Health Center | Hoopeston | Illinois |
United States | M D Anderson Cancer Center | Houston | Texas |
United States | Memorial Hermann Texas Medical Center | Houston | Texas |
United States | Indiana University/Melvin and Bren Simon Cancer Center | Indianapolis | Indiana |
United States | University of Iowa/Holden Comprehensive Cancer Center | Iowa City | Iowa |
United States | University of Florida Health Science Center - Jacksonville | Jacksonville | Florida |
United States | West Michigan Cancer Center | Kalamazoo | Michigan |
United States | Kaiser Permanente - Kensington Medical Center | Kensington | Maryland |
United States | University of Tennessee - Knoxville | Knoxville | Tennessee |
United States | Gundersen Lutheran Medical Center | La Crosse | Wisconsin |
United States | University of Arkansas for Medical Sciences | Little Rock | Arkansas |
United States | UCHealth Lone Tree Health Center | Lone Tree | Colorado |
United States | Los Angeles County-USC Medical Center | Los Angeles | California |
United States | USC / Norris Comprehensive Cancer Center | Los Angeles | California |
United States | University of Wisconsin Hospital and Clinics | Madison | Wisconsin |
United States | Marshfield Medical Center-Marshfield | Marshfield | Wisconsin |
United States | Carle Physician Group-Mattoon/Charleston | Mattoon | Illinois |
United States | Baptist Memorial Hospital and Cancer Center-Memphis | Memphis | Tennessee |
United States | Baptist Memorial Hospital for Women | Memphis | Tennessee |
United States | Hennepin County Medical Center | Minneapolis | Minnesota |
United States | Mobile Infirmary Medical Center | Mobile | Alabama |
United States | West Virginia University Healthcare | Morgantown | West Virginia |
United States | MUSC Health East Cooper | Mount Pleasant | South Carolina |
United States | ProHealth D N Greenwald Center | Mukwonago | Wisconsin |
United States | The Community Hospital | Munster | Indiana |
United States | Women's Diagnostic Center - Munster | Munster | Indiana |
United States | Vanderbilt Breast Center at One Hundred Oaks | Nashville | Tennessee |
United States | Vanderbilt University/Ingram Cancer Center | Nashville | Tennessee |
United States | Saint Peter's University Hospital | New Brunswick | New Jersey |
United States | Tulane University Health Sciences Center | New Orleans | Louisiana |
United States | University Medical Center New Orleans | New Orleans | Louisiana |
United States | Memorial Sloan Kettering Cancer Center | New York | New York |
United States | NYP/Columbia University Medical Center/Herbert Irving Comprehensive Cancer Center | New York | New York |
United States | NYP/Weill Cornell Medical Center | New York | New York |
United States | Helen F Graham Cancer Center | Newark | Delaware |
United States | Sentara Leigh Hospital | Norfolk | Virginia |
United States | Sentara Norfolk General Hospital | Norfolk | Virginia |
United States | ProHealth Oconomowoc Memorial Hospital | Oconomowoc | Wisconsin |
United States | Owensboro Health Mitchell Memorial Cancer Center | Owensboro | Kentucky |
United States | Fox Chase Cancer Center | Philadelphia | Pennsylvania |
United States | Pennsylvania Hospital | Philadelphia | Pennsylvania |
United States | Thomas Jefferson University Hospital | Philadelphia | Pennsylvania |
United States | Banner-University Medical Center Phoenix | Phoenix | Arizona |
United States | Mayo Clinic Hospital in Arizona | Phoenix | Arizona |
United States | University of Arizona College of Medicine Phoenix | Phoenix | Arizona |
United States | Valleywise Comprehensive Health Center - Phoenix | Phoenix | Arizona |
United States | Allegheny General Hospital | Pittsburgh | Pennsylvania |
United States | Riverview Medical Center/Booker Cancer Center | Red Bank | New Jersey |
United States | Mayo Clinic in Rochester | Rochester | Minnesota |
United States | University of Rochester | Rochester | New York |
United States | Park Nicollet Clinic - Saint Louis Park | Saint Louis Park | Minnesota |
United States | Regions Hospital | Saint Paul | Minnesota |
United States | University Hospital | San Antonio | Texas |
United States | Zuckerberg San Francisco General Hospital | San Francisco | California |
United States | Lewis Cancer and Research Pavilion at Saint Joseph's/Candler | Savannah | Georgia |
United States | Scottsdale Medical Imaging Limited | Scottsdale | Arizona |
United States | Swedish Medical Center-First Hill | Seattle | Washington |
United States | Sidney Kimmel Cancer Center Washington Township | Sewell | New Jersey |
United States | LSU Health Sciences Center at Shreveport | Shreveport | Louisiana |
United States | Ochsner LSU Health Saint Mary's Medical Center | Shreveport | Louisiana |
United States | Spartanburg Medical Center | Spartanburg | South Carolina |
United States | Spartanburg Medical Center - Mary Black Campus | Spartanburg | South Carolina |
United States | Sanford Thief River Falls Medical Center | Thief River Falls | Minnesota |
United States | Carle Cancer Center | Urbana | Illinois |
United States | Essentia Health Virginia Clinic | Virginia | Minnesota |
United States | Sentara Princess Anne Hospital | Virginia Beach | Virginia |
United States | MedStar Georgetown University Hospital | Washington | District of Columbia |
United States | UW Cancer Center at ProHealth Care | Waukesha | Wisconsin |
United States | Henry Ford West Bloomfield Hospital | West Bloomfield | Michigan |
United States | Wexford Health and Wellness Pavilion | Wexford | Pennsylvania |
United States | Wake Forest University Health Sciences | Winston-Salem | North Carolina |
United States | UMass Memorial Medical Center - University Campus | Worcester | Massachusetts |
Lead Sponsor | Collaborator |
---|---|
ECOG-ACRIN Cancer Research Group | Canadian Cancer Trials Group (CCTG), National Cancer Institute (NCI) |
United States, Argentina, Canada, Korea, Republic of, Puerto Rico,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Proportion of women diagnosed with an advanced breast cancer at any time during a period of 4.5 years from randomization, including the period of active screening and a period of follow up after the last screen | The cumulative proportions of participants experiencing the primary endpoint in the two study arms will be compared. The primary comparison of the two study arms will be approached from an Intent-to-Treat perspective and will be based on a two-sided test for comparing binomial proportions. | 4.5 years after last registration | |
Secondary | Agreement between local and expert study pathologists for all breast lesions (benign and malignant) biopsied during the five years of screening | Measures of agreement such as kappa statistics and concordance coefficients to assess the agreement of local and central pathology readings. In addition, the variability among local pathologists will be examined with respect to the degree of agreement with the central study interpretation. This analysis will utilize mixed models with random effects for local pathologists. There will be up to two central study independent pathologist interpretations for each representative diagnostic slide set. | Up to 8 years | |
Secondary | Breast Imaging-Reporting and Data System (BIRADS) imaging features | The correlation between BIRADS imaging features and histologic and genetic features, such as invasive ductal and invasive lobular histology, high grade, high stage at diagnosis, and aggressive genetic subtypes will be examined. Using data on patients with cancer, estimates of the correlation between the two sets of features (BIRADS imaging features and histologic/genetic features) will be derived. Cluster analysis will be used to identify clusters of patients based on imaging features and will examine the association of these clusters with histology and genetic features. Using data from the fu | Up to 8 years | |
Secondary | Breast-cancer-specific mortality | Breast-cancer-specific mortality between the two study arms will be estimated and compared. Information on cancer recurrence and mortality will be obtained for a period of at least 4.5-8 years on all study participants. Mortality rates will be estimated as the ratio of the number of breast cancer deaths during a time period to the number of person-years at risk. Person-years will be measured as time from randomization to breast cancer death or censoring. Cumulative mortality rates from breast cancer at the end of the study period in each arm will be compared via the relative risk (rate ratio). | Up to 8 years | |
Secondary | Centralized quality control (QC) monitoring program implementation | Centralized QC monitoring program for both DM and TM, which provides rapid feedback on image quality, using quantitative tools, taking advantage of the automated analysis of digital images. The QC program will provide an auditable trail of QC activities and image quality parameters, while at the same time reducing QC effort required by the technologist at the site. Constant monitoring of data from all sites will occur, and Root Cause Analysis will be performed for non-compliant items. The remote monitoring system will be evaluated in terms of its percent ?up-time?, technologist compliance (vi |
Up to 8 years | |
Secondary | Diagnostic and predictive performance of tomosynthesis mammography (TM) and digital mammography (DM) [AUC] | ROC analysis will be performed to compare the performance characteristics of DM vs TM at each screening visit | Up to 8 years | |
Secondary | Assess the predictive performance of tomosynthesis mammography (TM) and digital mammography (DM) | Compare the predictive characteristics (PPV,NPV,Sens, and Spec) of DM vs TM at each screening visit | Up to 8 years | |
Secondary | Health care costs (including diagnostic procedures and cancer care received) as the result of an episode of breast cancer screening by tomosynthesis mammography (TM) versus digital mammography (DM) | Rates of utilization of key diagnostic procedures (e.g. extra TM or DM views, Ultrasound, Short-term interval follow-up, surgical consultation, percutaneous biopsy with, needle-localized open surgical biopsy, breast MRI) will be estimated; Medicare reimbursement costs will be used to derive a standardized measure of cost per participant; and these costs will be compared across the two study arms. These measures of cost will be compared across study arms using non-parametric methods. | Up to 8 years | |
Secondary | Health care utilization (including cancer care received) of an episode of breast cancer screening by tomosynthesis mammography (TM) versus digital mammography (DM) | Rates of utilization of key diagnostic procedures (e.g. extra TM or DM views, Ultrasound, Short-term interval follow-up, surgical consultation, percutaneous biopsy with, needle-localized open surgical biopsy, breast MRI) will be estimated and compared across the two study arms. The comparisons will be made using regression modeling | Up to 8 years | |
Secondary | Histologically malignant (true positive cases) and benign lesions (false positive cases) | Classification of histologically benign-appearing lesions (false positive cases) will be explored as normal-like or tumor-like using the PAM50 gene expression assay subtype and low, medium, or high proliferation according to a PAM50 proliferation signature, and p53 mutant-like or wild-type-like according to a validated p53-dependent signature, and according to histological features. The benign-appearing (false positive) biopsies will be characterized using digital histologic analysis tools that capture percent of area represented by stroma, epithelium, and fat as well as the density of nuclei | Up to 8 years | |
Secondary | Prevalence of breast cancer subtypes (luminal A, luminal B, HER2+, basal-like) and p53 signature in the two arms | Prevalence of breast cancer subtypes (luminal A, luminal B, HER2+, basal-like) and p53 signature in the two arms will be estimated and compared, overall and stratified on whether cancers were detected through screening or as interval cancers. subtypes in each arm and to compare them across arms. The analysis will be performed overall, and stratified by screen detected or interval detected. Estimates of the prevalence of subtypes and confidence intervals will be developed for each screening round and for the full period of screening. The comparison of rates across arms will be based on multinom | Up to 8 years | |
Secondary | Proportion of women diagnosed with an ?advanced? breast cancer in the two arms | The potential effect of age, menopausal and hormonal status, breast density, and family cancer history will be assessed on the primary endpoint difference between the two arms. Regression modeling will be used to assess the effect of age, menopausal and hormonal status, breast density, and family cancer history. Multiple imputation will be used to handle missing data in the response and the covariates, and a sensitivity analysis to assumptions about the missing data will be performed. An exploratory analysis using alternative definitions of the primary endpoint will also be conducted in order | Up to 8 years | |
Secondary | Quality control (QC) tests useful for determination of image quality and those that are predictive of device failure | QC tests that are useful for determination of image quality and those that are predictive of device failure will be evaluated, in order to recommend an optimal QC program for TM. Tests that are most sensitive to changes in system performance will be established and tests that are inferior and/or redundant and can be eliminated. Changes will be tracked against site records of alterations or repairs to the system, recalibration and changes in imaging parameters. Changes in test results will be observed and if they are suggestive that remedial action is required, we will determine after such acti | Up to 8 years | |
Secondary | Rate of interval cancers | The rate of interval cancers for TM and DM will be compared and the mechanism of diagnosis for these interval cancers will be assessed with categorization by symptomatic vs asymptomatic, and how detected: diagnosed via physical examination, mammography, ultrasound (US), magnetic resonance imaging (MRI) or other technologies. Interval cancers are those that occur between screening examinations. Interval cancer rates for each screening occasion and over the full set of screens will be estimated using Wilson intervals and compared across arms using two-sided tests for binomial proportions. The di | Up to 8 years | |
Secondary | Recall rates | The recall rates for TM versus (vs) DM will be compared. Recall rates are defined as the number of screening examinations that are interpreted as BIRADS 0, 3, 4 and 5 divided by the total number of screening examinations. Recall rates for each screening occasion and over the full set of screens will be estimated using Wilson intervals and compared across arms using two-sided tests for binomial proportions. Logistic regression will be used to analyze potential differences across patient subsets. | Up to 8 years | |
Secondary | Biopsy rates | The biopsy rates for TM versus (vs) DM will be compared. biopsy rates are defined as the number of biopsies divided by the total number of screening examinations. rates for each screening occasion and over the full set of screens will be estimated using Wilson intervals and compared across arms using two-sided tests for binomial proportions. Logistic regression will be used to analyze potential differences across patient subsets | Up to 8 years | |
Secondary | Task-based measure of image quality | Task-based measures of image quality will be refined and implemented to assess the effects of technical parameters, including machine type, and detector spatial and contrast resolution on diagnostic accuracy for TM. the diagnostic accuracy of the resulting Task-based analysis, using mathematical observers, will be assessed from image information using techniques based on signal and noise transfer. | Up to 8 years | |
Secondary | Variability of quality control parameters | The variability of standard quality control parameters will be assessed and compared temporally, within, and across sites for both DM and TM. | Up to 8 years |
Status | Clinical Trial | Phase | |
---|---|---|---|
Completed |
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