Ignite Creation Date:
2025-12-24 @ 5:57 PM
Ignite Modification Date:
2025-12-29 @ 2:23 PM
Study NCT ID:
NCT01564368
Status:
COMPLETED
Last Update Posted:
2024-04-15
First Post:
2012-03-24
Is NOT Gene Therapy:
True
Has Adverse Events:
True
Brief Title:
DWI in Assessing Treatment Response in Patients With Breast Cancer Receiving Neoadjuvant Chemotherapy
Sponsor:
Organization:
Raw JSON
{'hasResults': True, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001943', 'term': 'Breast Neoplasms'}], 'ancestors': [{'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D001941', 'term': 'Breast Diseases'}, {'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}]}}, 'resultsSection': {'moreInfoModule': {'pointOfContact': {'email': 'info@acr.org', 'phone': '215-574-3150', 'title': 'Senior Director Clinical Research Administration', 'organization': 'American College of Radiology'}, 'certainAgreement': {'piSponsorEmployee': False, 'restrictiveAgreement': False}}, 'adverseEventsModule': {'timeFrame': 'From registration to surgery or off study, for events occurring within 30 days of each DW-MRI exam', 'eventGroups': [{'id': 'EG000', 'title': 'Diffusion Weighted-MRI', 'description': 'Participants on all arms of the I-SPY II trial will undergo diffusion-weighted magnetic resonance imaging as described in the ACRIN 6698 protocol. The experimental component/intervention is whether DW-MRI can predict therapeutic response in neoadjuvant treatment for breast cancer.\n\ndiffusion-weighted magnetic resonance imaging: diffusion-weighted magnetic resonance imaging examination and subsequent radiologist interpretation', 'otherNumAtRisk': 406, 'deathsNumAtRisk': 406, 'otherNumAffected': 0, 'seriousNumAtRisk': 406, 'deathsNumAffected': 0, 'seriousNumAffected': 0}], 'frequencyThreshold': '0'}, 'outcomeMeasuresModule': {'outcomeMeasures': [{'type': 'PRIMARY', 'title': 'Pathologic Complete Response (pCR)', 'denoms': [{'units': 'Participants', 'counts': [{'value': '227', 'groupId': 'OG000'}, {'value': '210', 'groupId': 'OG001'}, {'value': '186', 'groupId': 'OG002'}]}], 'groups': [{'id': 'OG000', 'title': 'Early Treatment Change', 'description': 'Participants who had both the pre-treatment (baseline) and the early-treatment (after 3 weekly doses of paclitaxel/taxane-based therapy) scans'}, {'id': 'OG001', 'title': 'Mid-Treatment Change', 'description': 'Participants who had both the pre-treatment (baseline) and the mid-treatment (after 12 weeks, between taxane and anthracycline regimens) scans'}, {'id': 'OG002', 'title': 'Post-Treatment Change', 'description': 'Participants who had both the pre-treatment (baseline) and the post-treatment (post-treatment after all chemotherapy, prior to surgery) scans'}], 'classes': [{'title': 'Pathological Complete Responders (pCR)', 'categories': [{'measurements': [{'value': '71', 'groupId': 'OG000'}, {'value': '70', 'groupId': 'OG001'}, {'value': '63', 'groupId': 'OG002'}]}]}, {'title': 'Non-Responders(pCR-)', 'categories': [{'measurements': [{'value': '156', 'groupId': 'OG000'}, {'value': '140', 'groupId': 'OG001'}, {'value': '123', 'groupId': 'OG002'}]}]}], 'analyses': [{'pValue': '0.484', 'groupIds': ['OG000'], 'paramType': 'area under the curve (AUC)', 'ciNumSides': 'ONE_SIDED', 'ciPctValue': '95', 'paramValue': '0.53', 'ciUpperLimit': '0.61', 'pValueComment': "Bonferroni's correction was used for multiple comparisons adjustment, where p\\<0.003 (0.05/15) was considered statistically significant.", 'estimateComment': "Receiver operating characteristic curve and AUC were estimated empirically, and its 95% CI was constructed using variance derived from DeLong's method", 'groupDescription': 'Receiver Operating Characteristic curves and the corresponding Area Under the Curve (AUC), were estimated for the change in Apparent Diffusion Coefficients (ADC1 - ADC0)/ADC0 (Test: %change in ADC; Reference: pCR) detect a difference of 0.15 between the AUC under H0: AUC=0.5 and an AUC under the alternative hypothesis of 0.65. It was assumed that the number of pCR non-responders would be approximately 2.7 times greater than the number of complete responders', 'statisticalMethod': 'Z-test', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'The empirical AUC was tested by using variance derived from the method of DeLong'}, {'pValue': '0.017', 'groupIds': ['OG001'], 'paramType': 'area under the curve', 'ciNumSides': 'ONE_SIDED', 'ciPctValue': '95', 'paramValue': '0.60', 'ciUpperLimit': '0.68', 'pValueComment': "Bonferroni's correction was used for multiple comparisons adjustment, where p\\<0.003 (0.05/15) was considered statistically significant.", 'estimateComment': "Receiver operating characteristic curve and AUC were estimated empirically, and its 95% CI was constructed using variance derived from DeLong's method", 'groupDescription': 'Receiver Operating Characteristic curves and the corresponding Area Under the Curve (AUC), were estimated for the change in Apparent Diffusion Coefficients (ADC2 - ADC0)/ADC0 (Test: %change in ADC; Reference: pCR) detect a difference of 0.15 between the AUC under H0: AUC=0.5 and an AUC under the alternative hypothesis of 0.65. It was assumed that the number of pCR non-responders would be approximately 2.7 times greater than the number of complete responders', 'statisticalMethod': 'Z-test', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'The empirical AUC was tested by using variance derived from the method of DeLong'}, {'pValue': '0.013', 'groupIds': ['OG002'], 'paramType': 'area under the curve', 'ciNumSides': 'ONE_SIDED', 'ciPctValue': '95', 'paramValue': '0.61', 'ciUpperLimit': '0.69', 'pValueComment': "Bonferroni's correction was used for multiple comparisons adjustment, where p\\<0.003 (0.05/15) is considered statistically significant.", 'estimateComment': "Receiver operating characteristic curve and AUC were estimated empirically, and its 95% CI was constructed using variance derived from DeLong's method", 'groupDescription': 'Receiver Operating Characteristic curves and the corresponding Area Under the Curve (AUC), were estimated for the change in Apparent Diffusion Coefficients (ADC3 - ADC0)/ADC0 (Test: %change in ADC; Reference: pCR) detect a difference of 0.15 between the AUC under H0: AUC=0.5 and an AUC under the alternative hypothesis of 0.65. It was assumed that the number of pCR non-responders would be approximately 2.7 times greater than the number of complete responders', 'statisticalMethod': 'Z-test', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'The empirical AUC was tested by using variance derived from the method of DeLong'}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'timeFrame': 'Surgery', 'description': 'Pathologic complete response (pCR) is defined as the lack of all signs of cancer in tissue samples removed during surgery after Neoadjuvant treatment for Breast cancer.\n\nie., no residual invasive disease in either breast or axillary lymph nodes after neoadjuvant therapy (ypT0/is, ypN0) Histopathologic analysis was performed using the Residual Cancer Burden system', 'unitOfMeasure': 'Participants', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Functional Tumor Volume (FTV) as a Predictor of Pathologic Complete Response (pCR)', 'denoms': [{'units': 'Participants', 'counts': [{'value': '227', 'groupId': 'OG000'}, {'value': '210', 'groupId': 'OG001'}, {'value': '186', 'groupId': 'OG002'}]}], 'groups': [{'id': 'OG000', 'title': 'Early Treatment Change', 'description': 'Participants who had both the pre-treatment (baseline) and the early-treatment (after 3 weekly doses of paclitaxel/taxane-based therapy) scans'}, {'id': 'OG001', 'title': 'Mid-Treatment Change', 'description': 'Participants who had both the pre-treatment (baseline) and the mid-treatment (after 12 weeks, between taxane and anthracycline regimens) scans'}, {'id': 'OG002', 'title': 'Post-Treatment Change', 'description': 'Participants who had both the pre-treatment (baseline) and the post-treatment (post-treatment after all chemotherapy, prior to surgery) scans'}], 'classes': [{'title': 'Pathological Complete Responders (pCR)', 'categories': [{'measurements': [{'value': '71', 'groupId': 'OG000'}, {'value': '70', 'groupId': 'OG001'}, {'value': '63', 'groupId': 'OG002'}]}]}, {'title': 'Non-Responders(pCR-)', 'categories': [{'measurements': [{'value': '156', 'groupId': 'OG000'}, {'value': '140', 'groupId': 'OG001'}, {'value': '123', 'groupId': 'OG002'}]}]}], 'analyses': [{'pValue': '<0.001', 'groupIds': ['OG000'], 'paramType': 'area under the curve', 'ciNumSides': 'ONE_SIDED', 'ciPctValue': '95', 'paramValue': '0.68', 'ciUpperLimit': '0.75', 'pValueComment': "Bonferroni's correction was used for multiple comparisons adjustment, where p\\<0.003 (0.05/15) was considered statistically significant.", 'estimateComment': "Receiver operating characteristic curve and AUC were estimated empirically, and its 95% CI was constructed using variance derived from DeLong's method", 'groupDescription': 'Receiver Operating Characteristic curves and the corresponding Area Under the Curve (AUC), were estimated for the change in functional tumor volumes (FTV1 - FTV0)/FTV0 (Test: %change in FTV; Reference: pCR) detect a difference of 0.15 between the AUC under H0: AUC=0.5 and an AUC under the alternative hypothesis of 0.65. It was assumed that the number of pCR non-responders would be approximately 2.7 times greater than the number of complete responders', 'statisticalMethod': 'Z-test', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'The empirical AUC was tested by using variance derived from the method of DeLong'}, {'pValue': '<0.001', 'groupIds': ['OG001'], 'paramType': 'area under the curve', 'ciNumSides': 'ONE_SIDED', 'ciPctValue': '95', 'paramValue': '0.63', 'ciUpperLimit': '0.71', 'pValueComment': "Bonferroni's correction was used for multiple comparisons adjustment, where p\\<0.003 (0.05/15) was considered statistically significant.", 'estimateComment': "Receiver operating characteristic curve and AUC were estimated empirically, and its 95% CI was constructed using variance derived from DeLong's method", 'groupDescription': 'Receiver Operating Characteristic curves and the corresponding Area Under the Curve (AUC), were estimated for the change in functional tumor volumes (FTV2 - FTV0)/FTV0 (Test: %change in FTV; Reference: pCR) detect a difference of 0.15 between the AUC under H0: AUC=0.5 and an AUC under the alternative hypothesis of 0.65. It was assumed that the number of pCR non-responders would be approximately 2.7 times greater than the number of complete responders', 'statisticalMethod': 'Z-test', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'The empirical AUC was tested by using variance derived from the method of DeLong'}, {'pValue': '<0.001', 'groupIds': ['OG002'], 'paramType': 'area under the curve', 'ciNumSides': 'ONE_SIDED', 'ciPctValue': '95', 'paramValue': '0.68', 'ciUpperLimit': '0.75', 'pValueComment': "Bonferroni's correction was used for multiple comparisons adjustment, where p\\<0.003 (0.05/15) was considered statistically significant.", 'estimateComment': "Receiver operating characteristic curve and AUC were estimated empirically, and its 95% CI was constructed using variance derived from DeLong's method", 'groupDescription': 'Receiver Operating Characteristic curves and the corresponding Area Under the Curve (AUC), were estimated for the change in functional tumor volumes (FTV3 - FTV0)/FTV0 (Test: %change in FTV; Reference: pCR) detect a difference of 0.15 between the AUC under H0: AUC=0.5 and an AUC under the alternative hypothesis of 0.65. It was assumed that the number of pCR non-responders would be approximately 2.7 times greater than the number of complete responders', 'statisticalMethod': 'Z-test', 'nonInferiorityType': 'SUPERIORITY', 'statisticalComment': 'The empirical AUC was tested by using variance derived from the method of DeLong'}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'timeFrame': 'Surgery', 'description': 'Pathologic complete response (pCR) is defined as the lack of all signs of cancer in tissue samples removed during surgery after Neoadjuvant treatment for Breast cancer.\n\nie., no residual invasive disease in either breast or axillary lymph nodes after neoadjuvant therapy (ypT0/is, ypN0) Histopathologic analysis was performed using the Residual Cancer Burden system Functional tumor volume (FTV) (units cm3) was computed by summing all tumor voxels meeting specific enhancement criteria, with customized thresholds for each site to account for variability in MR imaging systems', 'unitOfMeasure': 'Participants', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Determine the Accuracy of Predictive Models Including Covariates for Combined Measurement of Change in Tumor ADC Value, Change in Tumor Volume, and Other Variables', 'denoms': [{'units': 'Participants', 'counts': [{'value': '86', 'groupId': 'OG000'}, {'value': '86', 'groupId': 'OG001'}, {'value': '86', 'groupId': 'OG002'}]}], 'groups': [{'id': 'OG000', 'title': 'Full Combined Model', 'description': 'The data were split into a 60% training set (124 patients, randomly selected and stratified according to tumor subtype) and a 40% validation set (86 patients). Characteristics of the 86-patient test set were representative of the full analysis set, A predictive model, combining ΔADC, ΔFTV, and cancer subtype, was used to predict performance'}, {'id': 'OG001', 'title': 'Optimized Model', 'description': 'Backward selection was used to optimize the full model, and ΔFTV was eliminated, and the final prediction model retained ΔADC and tumor subtype as predictors.'}, {'id': 'OG002', 'title': 'ΔADC Alone', 'description': 'Tumor ADC change (the percentage change from the pretreatment to mid-treatment (ΔADC)) as the sole predictor of pCR'}], 'classes': [{'categories': [{'measurements': [{'value': '0.71', 'groupId': 'OG000', 'lowerLimit': '0.59', 'upperLimit': '0.84'}, {'value': '0.72', 'groupId': 'OG001', 'lowerLimit': '0.61', 'upperLimit': '0.83'}, {'value': '0.57', 'groupId': 'OG002', 'lowerLimit': '0.44', 'upperLimit': '0.70'}]}]}], 'analyses': [{'pValue': '0.032', 'groupIds': ['OG001', 'OG002'], 'groupDescription': 'AUC (optimized) = AUC (ΔADC)', 'statisticalMethod': 'z-test', 'nonInferiorityType': 'EQUIVALENCE', 'nonInferiorityComment': 'no equivalence margin was used.'}], 'paramType': 'NUMBER', 'timeFrame': 'baseline and mid-treatment', 'description': 'Accuracy will be measured as the Area under the Receiver Operating Characteristic Curve (AUC) Predictive logistic regression modeling was performed in 207 patients with complete mid-treatment ΔADC and ΔFTV data.\n\nTo build prediction models with ADC and other variables, a data-splitting approach was used where a randomly selected 60% of participants (124 patients), stratified according to pCR status and tumor subtype, were selected as the training data set and the rest (86 patients) as the test set. Logistic regression with backward variable selection was used to construct the prediction models, which were then applied to the remaining 40% of the data to obtain predictive scores for each participant.', 'unitOfMeasure': 'probability', 'dispersionType': '95% Confidence Interval', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Repeatability Coefficient (RC)Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'denoms': [{'units': 'Participants', 'counts': [{'value': '71', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Test-Retest Subjects', 'description': 'Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session. The patient was positioned normally (prone) and scanned with initial localization, T2W, and DWI acquisitions (2017 QIBA Profile). A single test/retest study was conducted for each consented subjects at either T0 or T1, with T0 specified as the preferred timepoint.'}], 'classes': [{'categories': [{'measurements': [{'value': '0.16', 'groupId': 'OG000', 'lowerLimit': '0.13', 'upperLimit': '0.19'}]}]}], 'paramType': 'NUMBER', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': 'within-subject standard deviation (wSD) Repeatability coefficient (RC): \\[RC = 2.77\\*wSD\\] (units: 10E-3 mm/sec\\^2)\n\nSmaller values of RC, bounded \\[0, ...), represent agreement', 'unitOfMeasure': '10E-3 mm/sec^2', 'dispersionType': '95% Confidence Interval', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Within-subject Coefficient of Variation (wCV) Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'denoms': [{'units': 'Participants', 'counts': [{'value': '71', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Test-Retest Subjects', 'description': 'Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session. The patient was positioned normally (prone) and scanned with initial localization, T2W, and DWI acquisitions (2017 QIBA Profile). A single test/retest study was conducted for each consented subjects at either T0 or T1, with T0 specified as the preferred timepoint.'}], 'classes': [{'categories': [{'measurements': [{'value': '4.8', 'groupId': 'OG000', 'lowerLimit': '4.0', 'upperLimit': '5.7'}]}]}], 'paramType': 'NUMBER', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': 'within-subject standard deviation (wSD) Within-subject coefficient of variation (wCV): \\[wCV = 100%\\*wSD/mean\\]\n\nSmaller values of wCV bounded for \\[0,...) represent better agreement', 'unitOfMeasure': 'coefficient of variation', 'dispersionType': '95% Confidence Interval', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'ICC Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'denoms': [{'units': 'Participants', 'counts': [{'value': '71', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Test-Retest Subjects', 'description': 'Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session. The patient was positioned normally (prone) and scanned with initial localization, T2W, and DWI acquisitions (2017 QIBA Profile). A single test/retest study was conducted for each consented subjects at either T0 or T1, with T0 specified as the preferred timepoint.'}], 'classes': [{'categories': [{'measurements': [{'value': '0.97', 'groupId': 'OG000', 'lowerLimit': '0.95', 'upperLimit': '0.98'}]}]}], 'paramType': 'NUMBER', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': 'Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session.\n\nIntraclass correlation coefficient (ICC) is derived from the analysis of variance (ANOVA) model estimates (Barnhart,Haber, Lin 2007),\n\nLarger values of ICC (bounded \\[-1,1\\]) represent agreement', 'unitOfMeasure': 'correlation coefficient', 'dispersionType': '95% Confidence Interval', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Agreement Index (AI) Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'denoms': [{'units': 'Participants', 'counts': [{'value': '71', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Test-Retest Subjects', 'description': 'Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session. The patient was positioned normally (prone) and scanned with initial localization, T2W, and DWI acquisitions (2017 QIBA Profile). A single test/retest study was conducted for each consented subjects at either T0 or T1, with T0 specified as the preferred timepoint.'}], 'classes': [{'categories': [{'measurements': [{'value': '0.83', 'groupId': 'OG000', 'lowerLimit': '0.76', 'upperLimit': '0.87'}]}]}], 'paramType': 'NUMBER', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': "Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session.\n\nAgreement index (AI): (Zhang, Wang, Duan - 2014) is based on the data's overall ranking. AI confidence intervals were obtained via bootstrap method Larger values AI (bounded \\[0.5,1\\]) represent agreement", 'unitOfMeasure': 'probability', 'dispersionType': '95% Confidence Interval', 'reportingStatus': 'POSTED'}]}, 'participantFlowModule': {'groups': [{'id': 'FG000', 'title': 'Diffusion Weighted-MRI', 'description': 'Participants on all arms of the I-SPY II trial will undergo diffusion-weighted magnetic resonance imaging as described in the ACRIN 6698 protocol. The experimental component/intervention is whether DW-MRI can predict therapeutic response (pathological Complete Response: pCR) in neoadjuvant treatment for breast cancer.'}], 'periods': [{'title': 'Overall Study', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '406'}]}, {'type': 'Randomized in Parent Study', 'achievements': [{'groupId': 'FG000', 'numSubjects': '272'}]}, {'type': 'Acceptable Baseline Imaging', 'achievements': [{'groupId': 'FG000', 'numSubjects': '263'}]}, {'type': 'Acceptable Post Baseline Image', 'achievements': [{'groupId': 'FG000', 'numSubjects': '242'}]}, {'type': 'Baseline and Early Treatment Usable', 'achievements': [{'groupId': 'FG000', 'numSubjects': '227'}]}, {'type': 'Baseline and Mid-treatment Usable', 'achievements': [{'groupId': 'FG000', 'numSubjects': '210'}]}, {'type': 'Baseline and Post-Treatment Usable', 'achievements': [{'groupId': 'FG000', 'numSubjects': '186'}]}, {'type': 'Usable Re-test Scan', 'achievements': [{'groupId': 'FG000', 'numSubjects': '71'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '242'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '164'}]}], 'dropWithdraws': [{'type': 'Ineligible', 'reasons': [{'groupId': 'FG000', 'numSubjects': '18'}]}, {'type': 'Not Randomized in Parent study', 'reasons': [{'groupId': 'FG000', 'numSubjects': '116'}]}, {'type': 'Baseline Imaging failed QC requirements', 'reasons': [{'groupId': 'FG000', 'numSubjects': '9'}]}, {'type': 'No Acceptable post-baseline imaging', 'reasons': [{'groupId': 'FG000', 'numSubjects': '21'}]}]}]}, 'baselineCharacteristicsModule': {'denoms': [{'units': 'Participants', 'counts': [{'value': '242', 'groupId': 'BG000'}]}], 'groups': [{'id': 'BG000', 'title': 'Diffusion Weighted-MRI', 'description': 'Participants on all arms of the I-SPY II trial with both a diffusion-weighted magnetic resonance imaging (DWI-MRI) scan at baseline and 1 post-baseline timepoint (early-treatment, mid-treatment, or post-treatment). The experimental component/intervention is whether DW-MRI can predict therapeutic response in women receiving neoadjuvant treatment for breast cancer.'}], 'measures': [{'title': 'Age, Continuous', 'classes': [{'categories': [{'measurements': [{'value': '48.1', 'spread': '10.4', 'groupId': 'BG000'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'years', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Sex/Gender, Customized', 'classes': [{'title': 'Female', 'categories': [{'measurements': [{'value': '242', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Ethnicity (NIH/OMB)', 'classes': [{'categories': [{'title': 'Hispanic or Latino', 'measurements': [{'value': '23', 'groupId': 'BG000'}]}, {'title': 'Not Hispanic or Latino', 'measurements': [{'value': '154', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '65', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Race (NIH/OMB)', 'classes': [{'categories': [{'title': 'American Indian or Alaska Native', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Asian', 'measurements': [{'value': '16', 'groupId': 'BG000'}]}, {'title': 'Native Hawaiian or Other Pacific Islander', 'measurements': [{'value': '1', 'groupId': 'BG000'}]}, {'title': 'Black or African American', 'measurements': [{'value': '26', 'groupId': 'BG000'}]}, {'title': 'White', 'measurements': [{'value': '173', 'groupId': 'BG000'}]}, {'title': 'More than one race', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '26', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}], 'populationDescription': 'Eligible randomized participants with a usable Baseline DWI-MRI and at least 1 other usable DWI scan at early-treatment, late-treatment, or pre-surgery'}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2014-04-30', 'size': 724911, 'label': 'Study Protocol and Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'Prot_SAP_000.pdf', 'typeAbbrev': 'Prot_SAP', 'uploadDate': '2019-07-03T18:08', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 406}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2012-08-27', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-03', 'completionDateStruct': {'date': '2020-01-14', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-03-18', 'studyFirstSubmitDate': '2012-03-24', 'resultsFirstSubmitDate': '2023-01-12', 'studyFirstSubmitQcDate': '2012-03-24', 'lastUpdatePostDateStruct': {'date': '2024-04-15', 'type': 'ACTUAL'}, 'resultsFirstSubmitQcDate': '2023-01-12', 'studyFirstPostDateStruct': {'date': '2012-03-27', 'type': 'ESTIMATED'}, 'resultsFirstPostDateStruct': {'date': '2023-02-10', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2018-07-19', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Pathologic Complete Response (pCR)', 'timeFrame': 'Surgery', 'description': 'Pathologic complete response (pCR) is defined as the lack of all signs of cancer in tissue samples removed during surgery after Neoadjuvant treatment for Breast cancer.\n\nie., no residual invasive disease in either breast or axillary lymph nodes after neoadjuvant therapy (ypT0/is, ypN0) Histopathologic analysis was performed using the Residual Cancer Burden system'}], 'secondaryOutcomes': [{'measure': 'Functional Tumor Volume (FTV) as a Predictor of Pathologic Complete Response (pCR)', 'timeFrame': 'Surgery', 'description': 'Pathologic complete response (pCR) is defined as the lack of all signs of cancer in tissue samples removed during surgery after Neoadjuvant treatment for Breast cancer.\n\nie., no residual invasive disease in either breast or axillary lymph nodes after neoadjuvant therapy (ypT0/is, ypN0) Histopathologic analysis was performed using the Residual Cancer Burden system Functional tumor volume (FTV) (units cm3) was computed by summing all tumor voxels meeting specific enhancement criteria, with customized thresholds for each site to account for variability in MR imaging systems'}, {'measure': 'Determine the Accuracy of Predictive Models Including Covariates for Combined Measurement of Change in Tumor ADC Value, Change in Tumor Volume, and Other Variables', 'timeFrame': 'baseline and mid-treatment', 'description': 'Accuracy will be measured as the Area under the Receiver Operating Characteristic Curve (AUC) Predictive logistic regression modeling was performed in 207 patients with complete mid-treatment ΔADC and ΔFTV data.\n\nTo build prediction models with ADC and other variables, a data-splitting approach was used where a randomly selected 60% of participants (124 patients), stratified according to pCR status and tumor subtype, were selected as the training data set and the rest (86 patients) as the test set. Logistic regression with backward variable selection was used to construct the prediction models, which were then applied to the remaining 40% of the data to obtain predictive scores for each participant.'}, {'measure': 'Repeatability Coefficient (RC)Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': 'within-subject standard deviation (wSD) Repeatability coefficient (RC): \\[RC = 2.77\\*wSD\\] (units: 10E-3 mm/sec\\^2)\n\nSmaller values of RC, bounded \\[0, ...), represent agreement'}, {'measure': 'Within-subject Coefficient of Variation (wCV) Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': 'within-subject standard deviation (wSD) Within-subject coefficient of variation (wCV): \\[wCV = 100%\\*wSD/mean\\]\n\nSmaller values of wCV bounded for \\[0,...) represent better agreement'}, {'measure': 'ICC Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': 'Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session.\n\nIntraclass correlation coefficient (ICC) is derived from the analysis of variance (ANOVA) model estimates (Barnhart,Haber, Lin 2007),\n\nLarger values of ICC (bounded \\[-1,1\\]) represent agreement'}, {'measure': 'Agreement Index (AI) Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors', 'timeFrame': 'baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)', 'description': "Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session.\n\nAgreement index (AI): (Zhang, Wang, Duan - 2014) is based on the data's overall ranking. AI confidence intervals were obtained via bootstrap method Larger values AI (bounded \\[0.5,1\\]) represent agreement"}]}, 'oversightModule': {'oversightHasDmc': True}, 'conditionsModule': {'keywords': ['stage II breast cancer', 'stage IIIA breast cancer', 'stage IIIB breast cancer', 'stage IIIC breast cancer', 'stage IV breast cancer', 'HER2-negative breast cancer', 'HER2-positive breast cancer'], 'conditions': ['Breast Cancer']}, 'referencesModule': {'references': [{'pmid': '3203132', 'type': 'BACKGROUND', 'citation': 'DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988 Sep;44(3):837-45.'}, {'pmid': '38180338', 'type': 'RESULT', 'citation': 'Li W, Partridge SC, Newitt DC, Steingrimsson J, Marques HS, Bolan PJ, Hirano M, Bearce BA, Kalpathy-Cramer J, Boss MA, Teng X, Zhang J, Cai J, Kontos D, Cohen EA, Mankowski WC, Liu M, Ha R, Pellicer-Valero OJ, Maier-Hein K, Rabinovici-Cohen S, Tlusty T, Ozery-Flato M, Parekh VS, Jacobs MA, Yan R, Sung K, Kazerouni AS, DiCarlo JC, Yankeelov TE, Chenevert TL, Hylton NM. Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge. Radiol Imaging Cancer. 2024 Jan;6(1):e230033. doi: 10.1148/rycan.230033.'}, {'pmid': '30179110', 'type': 'RESULT', 'citation': 'Partridge SC, Zhang Z, Newitt DC, Gibbs JE, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Romanoff J, Cimino L, Joe BN, Umphrey HR, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis JS, Esserman LJ, Hylton NM; ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators. Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial. Radiology. 2018 Dec;289(3):618-627. doi: 10.1148/radiol.2018180273. Epub 2018 Sep 4.'}, {'pmid': '32548294', 'type': 'RESULT', 'citation': 'Newitt DC, Amouzandeh G, Partridge SC, Marques HS, Herman BA, Ross BD, Hylton NM, Chenevert TL, Malyarenko DI. Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial. Tomography. 2020 Jun;6(2):177-185. doi: 10.18383/j.tom.2020.00008.'}, {'pmid': '30350329', 'type': 'RESULT', 'citation': 'Newitt DC, Zhang Z, Gibbs JE, Partridge SC, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Aliu S, Li W, Cimino L, Joe BN, Umphrey H, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis J, Esserman LJ, Hylton NM; ACRIN Trial Team and I-SPY 2 TRIAL Investigators. Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Magn Reson Imaging. 2019 Jun;49(6):1617-1628. doi: 10.1002/jmri.26539. Epub 2018 Oct 22.'}, {'pmid': '35314635', 'type': 'RESULT', 'citation': 'Partridge SC, Steingrimsson J, Newitt DC, Gibbs JE, Marques HS, Bolan PJ, Boss MA, Chenevert TL, Rosen MA, Hylton NM. Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial. Tomography. 2022 Mar 4;8(2):701-717. doi: 10.3390/tomography8020058.'}, {'pmid': '25758543', 'type': 'RESULT', 'citation': 'Newitt DC, Tan ET, Wilmes LJ, Chenevert TL, Kornak J, Marinelli L, Hylton N. Gradient nonlinearity correction to improve apparent diffusion coefficient accuracy and standardization in the american college of radiology imaging network 6698 breast cancer trial. J Magn Reson Imaging. 2015 Oct;42(4):908-19. doi: 10.1002/jmri.24883. Epub 2015 Mar 11.'}], 'seeAlsoLinks': [{'url': 'https://clinicaltrials.gov/ct2/show/NCT01564368', 'label': "National Cancer Institute's Clinical trial database"}]}, 'descriptionModule': {'briefSummary': 'RATIONALE: Imaging procedures, such as diffusion-weighted magnetic resonance imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), may help in evaluating how well patients with breast cancer respond to treatment.\n\nPURPOSE: This research trial studies DWI and DCE-MRI in assessing treatment response in patients with breast cancer undergoing neoadjuvant chemotherapy.', 'detailedDescription': 'OBJECTIVES:\n\nPrimary\n\n* To determine if the change in tumor apparent diffusion coefficient (ADC) value measured from each treatment timepoint to baseline is predictive of pathologic complete response (pCR).\n\nSecondary\n\n* To determine if the combined measurement of change in tumor ADC value, change in tumor volume, and change in peak signal-enhancement ratio (SER) is predictive of pCR.\n* To investigate the relative effectiveness of the individual measurements, change in tumor ADC value, change in tumor volume, and change in peak SER for predicting pCR in experimental treatment arms.\n* To assess the test-retest reproducibility of ADC metrics applied to breast tumors.\n\nOUTLINE: This is a multicenter study.\n\nPatients undergo diffusion-weighted magnetic resonance imaging (DWI) at baseline, after week 3 of neoadjuvant paclitaxel regimen, and prior to and after completion of 4 courses of neoadjuvant chemotherapy. Patients then undergo surgery. Patients undergo DWI prior to contrast administration for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).\n\nAfter completion of treatment procedure, patients are followed up for 5 years on the I-SPY 2 TRIAL.'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'DISEASE CHARACTERISTICS:\n\n* Meets I-SPY 2 TRIAL inclusion criteria\n\n * High-risk for recurrent disease\n\nPATIENT CHARACTERISTICS:\n\n* Able to tolerate imaging required by protocol\n\nPRIOR CONCURRENT THERAPY:\n\n* Not specified'}, 'identificationModule': {'nctId': 'NCT01564368', 'acronym': 'ACRIN6698', 'briefTitle': 'DWI in Assessing Treatment Response in Patients With Breast Cancer Receiving Neoadjuvant Chemotherapy', 'organization': {'class': 'NETWORK', 'fullName': 'American College of Radiology Imaging Network'}, 'officialTitle': 'Diffusion Weighted MR Imaging Biomarkers for Assessment of Breast Cancer Response to Neoadjuvant Treatment: A Sub-study of the I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And MoLecular Analysis)', 'orgStudyIdInfo': {'id': 'CDR0000729174'}, 'secondaryIdInfos': [{'id': 'ACRIN-6698', 'type': 'OTHER', 'domain': 'NCI CIP'}, {'id': 'U01CA080098', 'link': 'https://reporter.nih.gov/quickSearch/U01CA080098', 'type': 'NIH'}, {'id': 'U01CA079778', 'link': 'https://reporter.nih.gov/quickSearch/U01CA079778', 'type': 'NIH'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Diffusion Weighted-MRI', 'description': 'Participants on all arms of the I-SPY II trial will undergo diffusion-weighted magnetic resonance imaging as described in the ACRIN 6698 protocol. The experimental component/intervention is whether DW-MRI can predict therapeutic response in neoadjuvant treatment for breast cancer.', 'interventionNames': ['Procedure: diffusion-weighted magnetic resonance imaging']}], 'interventions': [{'name': 'diffusion-weighted magnetic resonance imaging', 'type': 'PROCEDURE', 'otherNames': ['functional MRI', 'DWI', 'diffusion-weighted MRI', 'DW-MRI'], 'description': 'diffusion-weighted magnetic resonance imaging examination and subsequent radiologist interpretation', 'armGroupLabels': ['Diffusion Weighted-MRI']}]}, 'contactsLocationsModule': {'locations': [{'zip': '35294', 'city': 'Birmingham', 'state': 'Alabama', 'country': 'United States', 'facility': 'University of Alabama at Birmingham', 'geoPoint': {'lat': 33.52066, 'lon': -86.80249}}, {'zip': '94143', 'city': 'San Francisco', 'state': 'California', 'country': 'United States', 'facility': 'University of California, San Francisco', 'geoPoint': {'lat': 37.77493, 'lon': -122.41942}}, {'zip': '55455', 'city': 'Minneapolis', 'state': 'Minnesota', 'country': 'United States', 'facility': 'University of Minnesota', 'geoPoint': {'lat': 44.97997, 'lon': -93.26384}}, {'zip': '97239', 'city': 'Portland', 'state': 'Oregon', 'country': 'United States', 'facility': 'Oregon Health and Science University', 'geoPoint': {'lat': 45.52345, 'lon': -122.67621}}, {'zip': '19104', 'city': 'Philadelphia', 'state': 'Pennsylvania', 'country': 'United States', 'facility': 'University of Pennsylvania', 'geoPoint': {'lat': 39.95238, 'lon': -75.16362}}, {'zip': '77030', 'city': 'Houston', 'state': 'Texas', 'country': 'United States', 'facility': 'University of Texas M.D. Anderson Cancer Center', 'geoPoint': {'lat': 29.76328, 'lon': -95.36327}}, {'zip': '98195', 'city': 'Seattle', 'state': 'Washington', 'country': 'United States', 'facility': 'University of Washington/SCCA', 'geoPoint': {'lat': 47.60621, 'lon': -122.33207}}], 'overallOfficials': [{'name': 'Nola M. Hylton, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of California, San Francisco'}]}, 'ipdSharingStatementModule': {'url': 'https://www.acrin.org/RESEARCHERS/POLICIES/DATAANDIMAGESHARINGPOLICY.aspx', 'infoTypes': ['STUDY_PROTOCOL', 'SAP'], 'timeFrame': '6mo post publication', 'ipdSharing': 'YES', 'description': 'See ACRIN data sharing Policy https://www.acrin.org/RESEARCHERS/POLICIES/DATAANDIMAGESHARINGPOLICY.aspx', 'accessCriteria': 'upon request'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'American College of Radiology Imaging Network', 'class': 'NETWORK'}, 'collaborators': [{'name': 'National Cancer Institute (NCI)', 'class': 'NIH'}], 'responsibleParty': {'type': 'SPONSOR'}}}}