Two-Level Factorial Pre-TomoBreast Pilot Study of Tomotherapy and Conventional Radiotherapy in Breast Cancer: Post Hoc Utility of a Mean Absolute Dose Deviation Penalty Score

Background: A 2-level factorial pilot study was conducted in 2007 just before starting a randomized clinical trial comparing tomotherapy and conventional radiotherapy (CR) to reduce cardiac and pulmonary adverse effects in breast cancer, considering tumor laterality (left/right), target volume (with/without nodal irradiation), surgery (tumorectomy/mastectomy), and patient position (prone/supine). The study was revisited using a penalty score based on the recently developed mean absolute dose deviation (MADD). Methods: Eight patients with a unique combination of laterality, nodal coverage, and surgery underwent dual tomotherapy and CR treatment planning in both prone and supine positions, providing 32 distinct combinations. The penalty score was applied using the weighted sum of the MADDs. The Lenth method for unreplicated 2-level factorial design was used in the analysis. Results: The Lenth analysis identified nodal irradiation as the active main effect penalizing the dosimetry by 1.14 Gy (P = 0.001). Other significant effects were left laterality (0.94 Gy), mastectomy (0.61 Gy), and interactions between left mastectomy (0.89 Gy) and prone mastectomy (0.71 Gy), with P-values between 0.005 and 0.05. Tomotherapy provided a small reduction in penalty (reduction of 0.54 Gy) through interaction with nodal irradiation (P = 0.080). Some effects approached significance with P-values > 0.05 and ≤ 0.10 for interactions of prone × mastectomy × left (0.60 Gy), nodal irradiation × mastectomy (0.59 Gy), and prone × left (0.55 Gy) and the main effect prone (0.52 Gy). Conclusions: The historical dosimetric analysis previously revealed the feasibility of tomotherapy, but a conclusion could not be made. The MADD-based score is promising, and a new analysis highlights the impact of factors and hierarchy of priorities that need to be addressed if major gains are to be attained.

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Ethnic disparities in the impact of breast cancer on the workforce: A pilot study.

Journal of Clinical Oncology ◽

10.1200/jco.2015.33.15_suppl.e17600 ◽

2015 ◽

Vol 33 (15_suppl) ◽

pp. e17600-e17600

Author(s):

Victoria Susana Blinder ◽

Carolyn E Eberle ◽

Sujata Patil ◽

Julia Ramirez ◽

Thelma McNish ◽

...

Keyword(s):

Breast Cancer ◽

Pilot Study ◽

Ethnic Disparities ◽

The Impact

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Recruiting breast cancer patients for mHealth research: Obstacles to clinic-based recruitment for a mobile phone app intervention study

Clinical Trials ◽

10.1177/1740774520939247 ◽

2020 ◽

Vol 17 (6) ◽

pp. 675-683

Author(s):

Alisha Gupta ◽

Gabrielle Ocker ◽

Philip I Chow

Keyword(s):

Breast Cancer ◽

Mental Health ◽

Pilot Study ◽

Cancer Patients ◽

Large Scale ◽

Newly Diagnosed ◽

Breast Cancer Patients ◽

Pilot Studies ◽

Staff Members ◽

The Impact

Background Nearly half of newly diagnosed breast cancer patients will report clinically significant symptoms of depression and/or anxiety within the first year of diagnosis. Research on the trajectory of distress in cancer patients suggests that targeting patients early in the diagnostic pathway could be particularly impactful. Given the recent rise of smartphone adoption, apps are a convenient and accessible platform from which to deliver mental health support; however, little research has examined their potential impact among newly diagnosed cancer patients. One reason is likely due to the obstacles associated with in-clinic recruitment of newly diagnosed cancer patients for mHealth pilot studies. Methods This article draws from our experiences of a recently completed pilot study to test a suite of mental health apps in newly diagnosed breast cancer patients. Recruitment strategies included in-clinic pamphlets, flyers, and direct communication with clinicians. Surgical oncologists and research staff members approached eligible patients after a medical appointment. Research team members met with patients to provide informed consent and review the study schedule. Results Four domains of in-clinic recruitment challenges emerged: (a) coordination with clinic staff, (b) perceived burden among breast cancer patients, (c) limitations regarding the adoption and use of technology, and (d) availability of resources. Potential solutions are provided for each challenge. Conclusion Recruitment of newly diagnosed cancer patients is a major challenge to conducting mobile intervention studies for researchers on a pilot-study budget. To realize the impact of mobile interventions for the most vulnerable cancer patient populations, health researchers must address barriers to in-clinic recruitment to provide vital preliminary data in proposals of large-scale research projects.

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The impact of high-intensity interval training exercise on breast cancer survivors: a pilot study to explore fitness, cardiac regulation and biomarkers of the stress systems

BMC Cancer ◽

10.1186/s12885-020-07295-1 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Kellie Toohey ◽

Kate Pumpa ◽

Andrew McKune ◽

Julie Cooke ◽

Marijke Welvaert ◽

...

Keyword(s):

Breast Cancer ◽

Pilot Study ◽

Cancer Survivors ◽

High Intensity ◽

Breast Cancer Survivors ◽

Interval Training ◽

High Intensity Interval Training ◽

Cardiac Regulation ◽

High Intensity Interval ◽

The Impact

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The Impact of an Antireflux Catheter on Target Volume Particulate Distribution in Liver-Directed Embolotherapy: A Pilot Study

Journal of Vascular and Interventional Radiology ◽

10.1016/j.jvir.2015.01.029 ◽

2015 ◽

Vol 26 (5) ◽

pp. 660-669 ◽

Cited By ~ 17

Author(s):

Alexander S. Pasciak ◽

James H. McElmurray ◽

Austin C. Bourgeois ◽

R. Eric Heidel ◽

Yong C. Bradley

Keyword(s):

Pilot Study ◽

Target Volume ◽

Particulate Distribution ◽

The Impact

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A Pilot Study Addressing the Impact of Religious Practice on Quality of Life of Breast Cancer Patients During Chemotherapy

Journal of Religion and Health ◽

10.1007/s10943-011-9468-6 ◽

2011 ◽

Vol 52 (1) ◽

pp. 184-193 ◽

Cited By ~ 9

Author(s):

Carlos Eduardo Paiva ◽

Bianca Sakamoto Ribeiro Paiva ◽

Rafael Amaral de Castro ◽

Cristiano de Pádua Souza ◽

Yara Cristina de Paiva Maia ◽

...

Keyword(s):

Breast Cancer ◽

Quality Of Life ◽

Pilot Study ◽

Cancer Patients ◽

Religious Practice ◽

Breast Cancer Patients ◽

The Impact

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Abstract A52: A pilot study to examine patient awareness and provider discussion of the impact of cancer treatment on fertility in a registry-based sample of African American women with breast cancer

10.1158/1055-9965.disp-11-a52 ◽

2011 ◽

Author(s):

Juliette Christie ◽

Tuya Pal ◽

Gwendolyn Quinn ◽

Patrice Fleming ◽

Caitlin Stowe ◽

...

Keyword(s):

Breast Cancer ◽

African American ◽

Pilot Study ◽

Cancer Treatment ◽

African American Women ◽

American Women ◽

Patient Awareness ◽

The Impact

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A pilot study to examine patient awareness and provider discussion of the impact of cancer treatment on fertility in a registry-based sample of African American women with breast cancer

Supportive Care in Cancer ◽

10.1007/s00520-012-1380-4 ◽

2012 ◽

Vol 20 (10) ◽

pp. 2559-2564 ◽

Cited By ~ 12

Author(s):

Susan T. Vadaparampil ◽

Juliette Christie ◽

Gwendolyn P. Quinn ◽

Patrice Fleming ◽

Caitlin Stowe ◽

...

Keyword(s):

Breast Cancer ◽

African American ◽

Pilot Study ◽

Cancer Treatment ◽

African American Women ◽

American Women ◽

Patient Awareness ◽

The Impact

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Radiomics Analysis on Contrast-Enhanced Spectral Mammography Images for Breast Cancer Diagnosis: A Pilot Study

Entropy ◽

10.3390/e21111110 ◽

2019 ◽

Vol 21 (11) ◽

pp. 1110 ◽

Cited By ~ 1

Author(s):

Liliana Losurdo ◽

Annarita Fanizzi ◽

Teresa Maria A. Basile ◽

Roberto Bellotti ◽

Ubaldo Bottigli ◽

...

Keyword(s):

Breast Cancer ◽

Pilot Study ◽

Support Vector ◽

Svm Classifier ◽

Textural Features ◽

Breast Lesions ◽

Haar Transform ◽

Statistical Measures ◽

Contrast Enhanced ◽

The Impact

Contrast-enhanced spectral mammography is one of the latest diagnostic tool for breast care; therefore, the literature is poor in radiomics image analysis useful to drive the development of automatic diagnostic support systems. In this work, we propose a preliminary exploratory analysis to evaluate the impact of different sets of textural features in the discrimination of benign and malignant breast lesions. The analysis is performed on 55 ROIs extracted from 51 patients referred to Istituto Tumori “Giovanni Paolo II” of Bari (Italy) from the breast cancer screening phase between March 2017 and June 2018. We extracted feature sets by calculating statistical measures on original ROIs, gradiented images, Haar decompositions of the same original ROIs, and on gray-level co-occurrence matrices of the each sub-ROI obtained by Haar transform. First, we evaluated the overall impact of each feature set on the diagnosis through a principal component analysis by training a support vector machine classifier. Then, in order to identify a sub-set for each set of features with higher diagnostic power, we developed a feature importance analysis by means of wrapper and embedded methods. Finally, we trained an SVM classifier on each sub-set of previously selected features to compare their classification performances with respect to those of the overall set. We found a sub-set of significant features extracted from the original ROIs with a diagnostic accuracy greater than 80 % . The features extracted from each sub-ROI decomposed by two levels of Haar transform were predictive only when they were all used without any selection, reaching the best mean accuracy of about 80 % . Moreover, most of the significant features calculated by HAAR decompositions and their GLCMs were extracted from recombined CESM images. Our pilot study suggested that textural features could provide complementary information about the characterization of breast lesions. In particular, we found a sub-set of significant features extracted from the original ROIs, gradiented ROI images, and GLCMs calculated from each sub-ROI previously decomposed by the Haar transform.

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