Publications by authors named "Todd McNutt"

126 Publications

Comparison of Multimodal Therapies and Outcomes Among Patients With High-Risk Prostate Cancer With Adverse Clinicopathologic Features.

JAMA Netw Open 2021 Jul 1;4(7):e2115312. Epub 2021 Jul 1.

Department of Urology, Brady Urological Institute, Johns Hopkins University, Baltimore, Maryland.

Importance: The optimal management strategy for high-risk prostate cancer and additional adverse clinicopathologic features remains unknown.

Objective: To compare clinical outcomes among patients with high-risk prostate cancer after definitive treatment.

Design, Setting, And Participants: This retrospective cohort study included patients with high-risk prostate cancer (as defined by the National Comprehensive Cancer Network [NCCN]) and at least 1 adverse clinicopathologic feature (defined as any primary Gleason pattern 5 on biopsy, clinical T3b-4 disease, ≥50% cores with biopsy results positive for prostate cancer, or NCCN ≥2 high-risk features) treated between 2000 and 2014 at 16 tertiary centers. Data were analyzed in November 2020.

Exposures: Radical prostatectomy (RP), external beam radiotherapy (EBRT) with androgen deprivation therapy (ADT), or EBRT plus brachytherapy boost (BT) with ADT. Guideline-concordant multimodal treatment was defined as RP with appropriate use of multimodal therapy (optimal RP), EBRT with at least 2 years of ADT (optimal EBRT), or EBRT with BT with at least 1 year ADT (optimal EBRT with BT).

Main Outcomes And Measures: The primary outcome was prostate cancer-specific mortality; distant metastasis was a secondary outcome. Differences were evaluated using inverse probability of treatment weight-adjusted Fine-Gray competing risk regression models.

Results: A total of 6004 men (median [interquartile range] age, 66.4 [60.9-71.8] years) with high-risk prostate cancer were analyzed, including 3175 patients (52.9%) who underwent RP, 1830 patients (30.5%) who underwent EBRT alone, and 999 patients (16.6%) who underwent EBRT with BT. Compared with RP, treatment with EBRT with BT (subdistribution hazard ratio [sHR] 0.78, [95% CI, 0.63-0.97]; P = .03) or with EBRT alone (sHR, 0.70 [95% CI, 0.53-0.92]; P = .01) was associated with significantly improved prostate cancer-specific mortality; there was no difference in prostate cancer-specific mortality between EBRT with BT and EBRT alone (sHR, 0.89 [95% CI, 0.67-1.18]; P = .43). No significant differences in prostate cancer-specific mortality were found across treatment cohorts among 2940 patients who received guideline-concordant multimodality treatment (eg, optimal EBRT alone vs optimal RP: sHR, 0.76 [95% CI, 0.52-1.09]; P = .14). However, treatment with EBRT alone or EBRT with BT was consistently associated with lower rates of distant metastasis compared with treatment with RP (eg, EBRT vs RP: sHR, 0.50 [95% CI, 0.44-0.58]; P < .001).

Conclusions And Relevance: These findings suggest that among patients with high-risk prostate cancer and additional unfavorable clinicopathologic features receiving guideline-concordant multimodal therapy, prostate cancer-specific mortality outcomes were equivalent among those treated with RP, EBRT, and EBRT with BT, although distant metastasis outcomes were more favorable among patients treated with EBRT and EBRT with BT. Optimal multimodality treatment is critical for improving outcomes in patients with high-risk prostate cancer.
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http://dx.doi.org/10.1001/jamanetworkopen.2021.15312DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8251338PMC
July 2021

Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations.

Phys Med Biol 2021 Jun 17;66(12). Epub 2021 Jun 17.

Medical Physics, San Raffaele Scientific Institute, Milano, Italy.

For decades, dose-volume information for segmented anatomy has provided the essential data for correlating radiotherapy dosimetry with treatment-induced complications. Dose-volume information has formed the basis for modelling those associations via normal tissue complication probability (NTCP) models and for driving treatment planning. Limitations to this approach have been identified. Many studies have emerged demonstrating that the incorporation of information describing the spatial nature of the dose distribution, and potentially its correlation with anatomy, can provide more robust associations with toxicity and seed more general NTCP models. Such approaches are culminating in the application of computationally intensive processes such as machine learning and the application of neural networks. The opportunities these approaches have for individualising treatment, predicting toxicity and expanding the solution space for radiation therapy are substantial and have clearly widespread and disruptive potential. Impediments to reaching that potential include issues associated with data collection, model generalisation and validation. This review examines the role of spatial models of complication and summarises relevant published studies. Sources of data for these studies, appropriate statistical methodology frameworks for processing spatial dose information and extracting relevant features are described. Spatial complication modelling is consolidated as a pathway to guiding future developments towards effective, complication-free radiotherapy treatment.
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http://dx.doi.org/10.1088/1361-6560/ac0681DOI Listing
June 2021

In Reply to Nieder.

Int J Radiat Oncol Biol Phys 2021 Jun;110(2):614-615

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

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http://dx.doi.org/10.1016/j.ijrobp.2020.12.057DOI Listing
June 2021

Patterns of Clinical Progression in Radiorecurrent High-risk Prostate Cancer.

Eur Urol 2021 Aug 10;80(2):142-146. Epub 2021 May 10.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

The natural history of radiorecurrent high-risk prostate cancer (HRPCa) is not well-described. To better understand its clinical course, we evaluated rates of distant metastases (DM) and prostate cancer-specific mortality (PCSM) in a cohort of 978 men with radiorecurrent HRPCa who previously received either external beam radiation therapy (EBRT, n = 654, 67%) or EBRT + brachytherapy (EBRT + BT, n = 324, 33%) across 15 institutions from 1997 to 2015. In men who did not die, median follow-up after treatment was 8.9 yr and median follow-up after biochemical recurrence (BCR) was 3.7 yr. Local and systemic therapy salvage, respectively, were delivered to 21 and 390 men after EBRT, and eight and 103 men after EBRT + BT. Overall, 435 men developed DM, and 248 were detected within 1 yr of BCR. Measured from time of recurrence, 5-yr DM rates were 50% and 34% after EBRT and EBRT + BT, respectively. Measured from BCR, 5-yr PCSM rates were 27% and 29%, respectively. Interval to BCR was independently associated with DM (p < 0.001) and PCSM (p < 0.001). These data suggest that radiorecurrent HRPCa has an aggressive natural history and that DM is clinically evident early after BCR. These findings underscore the importance of further investigations into upfront risk assessment and prompt systemic evaluation upon recurrence in HRPCa. PATIENT SUMMARY: High-risk prostate cancer that recurs after radiation therapy is an aggressive disease entity and spreads to other parts of the body (metastases). Some 60% of metastases occur within 1 yr. Approximately 30% of these patients die from their prostate cancer.
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http://dx.doi.org/10.1016/j.eururo.2021.04.035DOI Listing
August 2021

External Validation of the Bone Metastases Ensemble Trees for Survival (BMETS) Machine Learning Model to Predict Survival in Patients With Symptomatic Bone Metastases.

JCO Clin Cancer Inform 2021 03;5:304-314

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.

Purpose: The Bone Metastases Ensemble Trees for Survival (BMETS) model uses a machine learning algorithm to estimate survival time following consultation for palliative radiation therapy for symptomatic bone metastases (SBM). BMETS was developed at a tertiary-care, academic medical center, but its validity and stability when applied to external data sets are unknown.

Patients And Methods: Patients treated with palliative radiation therapy for SBM from May 2013 to May 2016 at two hospital-based community radiation oncology clinics were included, and medical records were retrospectively reviewed to collect model covariates and survival time. The Kaplan-Meier method was used to estimate overall survival from consultation to death or last follow-up. Model discrimination was estimated using time-dependent area under the curve (tAUC), which was calculated using survival predictions from BMETS based on the initial training data set.

Results: A total of 216 sites of SBM were treated in 182 patients. Most common histologies were breast (27%), lung (23%), and prostate (23%). Compared with the BMETS training set, the external validation population was older (mean age, 67 62 years; < .001), had more primary breast (27% 19%; = .03) and prostate cancer (20% 12%; = .01), and survived longer (median, 10.7 6.4 months). When the BMETS model was applied to the external data set, tAUC values at 3, 6, and 12 months were 0.82, 0.77, and 0.77, respectively. When refit with data from the combined training and external validation sets, tAUC remained 0.79.

Conclusion: BMETS maintained high discriminative ability when applied to an external validation set and when refit with new data, supporting its generalizability, stability, and the feasibility of dynamic modeling.
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http://dx.doi.org/10.1200/CCI.20.00128DOI Listing
March 2021

Longitudinal Trends of Financial Toxicity in Patients With Lung Cancer: A Prospective Cohort Study.

JCO Oncol Pract 2021 Feb 8:OP2000721. Epub 2021 Feb 8.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.

Background: Cancer therapy is associated with severe financial burden. However, the magnitude and longitudinal patient relationship with financial toxicity (FT) in the initial course of therapy is unclear.

Methods: Patients with stage II-IV lung cancer were recruited in a prospective longitudinal study between July 2018 and March 2020. FT was measured via the validated COmprehensive Score for financial Toxicity (COST) at the time of cancer diagnosis and at 6-month follow-up (6MFU). 6MFU data were compared with corresponding baseline data. A lower COST score indicates increased financial hardship.

Results: At the time of analysis, 215 agreed to participate. Subsequently, 112 patients completed 6MFU. On average, slightly more FT was observed at diagnosis compared with 6MFU (median COST 25 COST 27; < .001); however, individual patients experienced large changes in FT. At 6MFU, 27.7% of patients had made financial sacrifices to pay for treatment but only 4.5% refused medical care based on cost. Median reported out-of-pocket (OOP) costs for the initial 6 months of cancer treatment was $2,496 (range, $0-25,900). Risk factors for FT at diagnosis were unique from risk factors at 6MFU. Actual OOP expenses were not correlated with FT; however, inability to predict upcoming treatment expenses resulted in higher FT at 6MFU.

Discussion: FT is a pervasive challenge during the initiation of lung cancer treatment. Few patients are willing to sacrifice medical care regardless of the cost. Risk factors for FT evolve, resulting in unique interventional targets throughout therapy.
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http://dx.doi.org/10.1200/OP.20.00721DOI Listing
February 2021

Patient-Reported Outcome Measures and Dosimetric Correlates for Early Detection of Acute Radiation Therapy-Related Esophagitis.

Pract Radiat Oncol 2021 May-Jun;11(3):185-192. Epub 2020 Oct 31.

Department of Medicine, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, and Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.

Background: We investigate the time to and clinical factors associated with patient-reported difficulty swallowing in lung cancer patients treated with radiation therapy (RT).

Methods: Between October 2016 and October 2019, lung cancer patients treated with conventionally fractionated RT at a tertiary cancer center were identified. Weekly, patients reported difficulty swallowing (patient-reported outcome version of the Common Terminology Criteria for Adverse Events [PRO-CTCAE] v.1: 0-none, 1-mild, 2-moderate, 3-severe, 4-very severe). Physicians graded dysphagia (CTCAE v.4: 0-none, 1-symptoms without altered intake, 2-symptomatic; altered eating/swallowing, 3-severely altered eating/swallowing, 4-life-threatening consequences, 5-death). Tumor-related difficulty swallowing was not recorded at baseline; thus, patients reporting ≥moderate symptoms ≤7 days of RT start were excluded. We evaluated the time to new patient reports of ≥moderate difficulty swallowing and CTCAE grade 2+ dysphagia and development over time using the cumulative incidence method. Multivariable logistic regression evaluated associations between clinical factors, esophageal V60, and development of esophageal symptoms.

Results: Of the 200 patients identified: median age was 69 years, 52% were male, and 89% had stage III+ disease. Patients received a median of 63 Gy with chemotherapy (91.5%). At least moderate difficulty swallowing during RT was reported by 76 of 200 patients (38%); clinicians rated dysphagia as altering oral intake or worse for 26 of 200 (13%). Median time to first report of symptoms was 21 days (interquartile ratio [IQR], 18-34.5) for the 76 patients who reported ≥moderate symptoms and 33 days (IQR, 24-42) in the 26 patients whose provider reported grade 2+ dysphagia. The 30-day incidence of patient-reported ≥moderate swallowing difficulty and provider grade 2+ dysphagia was 26% (95% CI: 20%-32%) and 6% (95% CI: 3%-9%), respectively. Esophageal V60 >7 % was the clinical factor most associated with patient-reported ≥moderate esophageal symptoms (odds ratio 6.1, 95% CI: 3.0-12.3).

Conclusions: Patients report at least moderate difficulty swallowing more often and earlier than providers report grade 2+ dysphagia. Esophageal V60 ≥7% was most associated with development of moderate severity or worse patient-reported swallowing difficulty.
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http://dx.doi.org/10.1016/j.prro.2020.10.009DOI Listing
October 2020

Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate.

JAMA Oncol 2020 12;6(12):1912-1920

Department of Radiation Oncology, Penn State Cancer Institute, Hershey, Pennsylvania.

Importance: In 2016, the American Joint Committee on Cancer (AJCC) established criteria to evaluate prediction models for staging. No localized prostate cancer models were endorsed by the Precision Medicine Core committee, and 8th edition staging was based on expert consensus.

Objective: To develop and validate a pretreatment clinical prognostic stage group system for nonmetastatic prostate cancer.

Design, Setting, And Participants: This multinational cohort study included 7 centers from the United States, Canada, and Europe, the Shared Equal Access Regional Cancer Hospital (SEARCH) Veterans Affairs Medical Centers collaborative (5 centers), and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry (43 centers) (the STAR-CAP cohort). Patients with cT1-4N0-1M0 prostate adenocarcinoma treated from January 1, 1992, to December 31, 2013 (follow-up completed December 31, 2017). The STAR-CAP cohort was randomly divided into training and validation data sets; statisticians were blinded to the validation data until the model was locked. A Surveillance, Epidemiology, and End Results (SEER) cohort was used as a second validation set. Analysis was performed from January 1, 2018, to November 30, 2019.

Exposures: Curative intent radical prostatectomy (RP) or radiotherapy with or without androgen deprivation therapy.

Main Outcomes And Measures: Prostate cancer-specific mortality (PCSM). Based on a competing-risk regression model, a points-based Score staging system was developed. Model discrimination (C index), calibration, and overall performance were assessed in the validation cohorts.

Results: Of 19 684 patients included in the analysis (median age, 64.0 [interquartile range (IQR), 59.0-70.0] years), 12 421 were treated with RP and 7263 with radiotherapy. Median follow-up was 71.8 (IQR, 34.3-124.3) months; 4078 (20.7%) were followed up for at least 10 years. Age, T category, N category, Gleason grade, pretreatment serum prostate-specific antigen level, and the percentage of positive core biopsy results among biopsies performed were included as variables. In the validation set, predicted 10-year PCSM for the 9 Score groups ranged from 0.3% to 40.0%. The 10-year C index (0.796; 95% CI, 0.760-0.828) exceeded that of the AJCC 8th edition (0.757; 95% CI, 0.719-0.792), which was improved across age, race, and treatment modality and within the SEER validation cohort. The Score system performed similarly to individualized random survival forest and interaction models and outperformed National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk grouping 3- and 4-tier classification systems (10-year C index for NCCN 3-tier, 0.729; for NCCN 4-tier, 0.746; for Score, 0.794) as well as CAPRA (10-year C index for CAPRA, 0.760; for Score, 0.782).

Conclusions And Relevance: Using a large, diverse international cohort treated with standard curative treatment options, a proposed AJCC-compliant clinical prognostic stage group system for prostate cancer has been developed. This system may allow consistency of reporting and interpretation of results and clinical trial design.
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http://dx.doi.org/10.1001/jamaoncol.2020.4922DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582232PMC
December 2020

Isolated progression of metastatic lung cancer: Clinical outcomes associated with definitive radiotherapy.

Cancer 2020 10 30;126(20):4572-4583. Epub 2020 Jul 30.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Background: Progressive, metastatic non-small cell lung cancer (NSCLC) often requires the initiation of new systemic therapy. However, in patients with NSCLC that is oligoprogressive (≤3 lesions), local radiotherapy (RT) may allow for the eradication of resistant microclones and, therefore, the continuation of otherwise effective systemic therapy.

Methods: Patients treated from 2008 to 2019 with definitive doses of RT to all sites of intracranial or extracranial oligoprogression without a change in systemic therapy were identified. Radiographic progression-free survival (rPFS) and time to new therapy (TNT) were measured. Associations between baseline clinical and treatment-related variables were correlated with progression-free survival via Cox proportional hazards modeling.

Results: Among 198 unique patients, 253 oligoprogressive events were identified. Intracranial progression occurred in 51% of the patients, and extracranial progression occurred in 49%. In the entire cohort, the median rPFS was 7.9 months (95% CI, 6.5-10.0 months), and the median TNT was 8.8 months (95% CI, 7.2-10.9 months). On adjusted modeling, patients with the following disease characteristics were associated with better rPFS: better performance status (P = .003), fewer metastases (P = .03), longer time to oligoprogression (P = .009), and fewer previous systemic therapies (P = .02). Having multiple sites of oligoprogression was associated with worse rPFS (P < .001).

Conclusions: In select patients with oligoprogression, definitive RT is a feasible treatment option to delay the initiation of next-line systemic therapies, which have more limited response rates and efficacy. Further randomized prospective data may help to validate these findings and identify which patients are most likely to benefit.
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http://dx.doi.org/10.1002/cncr.33109DOI Listing
October 2020

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

Int J Radiat Oncol Biol Phys 2020 11 22;108(3):554-563. Epub 2020 May 22.

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Purpose: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic covariates. To establish its relative clinical utility, we compared BMETS with 2 simpler Cox regression models used in this setting.

Methods And Materials: For 492 bone sites in 397 patients evaluated for palliative radiation therapy (RT) for SBM from January 2007 to January 2013, data for 27 clinical variables were collected. These covariates and the primary outcome of time from consultation to death were used to build BMETS using random survival forests. We then performed Cox regressions as per 2 validated models: Chow's 3-item (C-3) and Westhoff's 2-item (W-2) tools. Model performance was assessed using cross-validation procedures and measured by time-dependent area under the curve (tAUC) for all 3 models. For temporal validation, a separate data set comprised of 104 bone sites treated in 85 patients in 2018 was used to estimate tAUC from BMETS.

Results: Median survival was 6.4 months. Variable importance was greatest for performance status, blood cell counts, recent systemic therapy type, and receipt of concurrent nonbone palliative RT. tAUC at 3, 6, and 12 months was 0.83, 0.81, and 0.81, respectively, suggesting excellent discrimination of BMETS across postconsultation time points. BMETS outperformed simpler models at each time, with respective tAUC at each time of 0.78, 0.76, and 0.74 for the C-3 model and 0.80, 0.78, and 0.77 for the W-2 model. For the temporal validation set, respective tAUC was similarly high at 0.86, 0.82, and 0.78.

Conclusions: For patients with SBM, BMETS improved survival predictions versus simpler traditional models. Model performance was maintained when applied to a temporal validation set. To facilitate clinical use, we developed a web platform for data entry and display of BMETS-predicted survival probabilities.
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http://dx.doi.org/10.1016/j.ijrobp.2020.05.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954525PMC
November 2020

Low-Dose Image-Guided Pediatric CNS Radiation Therapy: Final Analysis From a Prospective Low-Dose Cone-Beam CT Protocol From a Multinational Pediatrics Consortium.

Technol Cancer Res Treat 2020 Jan-Dec;19:1533033820920650

Department of Radiation Oncology and Molecular Radiation Sciences, University of Minnesota, Minneapolis, MN, USA.

Background: Lower-dose cone-beam computed tomography protocols for image-guided radiotherapy may permit target localization while minimizing radiation exposure. We prospectively evaluated a lower-dose cone-beam protocol for central nervous system image-guided radiotherapy across a multinational pediatrics consortium.

Methods: Seven institutions prospectively employed a lower-dose cone-beam computed tomography central nervous system protocol (weighted average dose 0.7 mGy) for patients ≤21 years. Treatment table shifts between setup with surface lasers versus cone-beam computed tomography were used to approximate setup accuracy, and vector magnitudes for these shifts were calculated. Setup group mean, interpatient, interinstitution, and random error were estimated, and clinical factors were compared by mixed linear modeling.

Results: Among 96 patients, with 2179 pretreatment cone-beam computed tomography acquisitions, median age was 9 years (1-20). Setup parameters were 3.13, 3.02, 1.64, and 1.48 mm for vector magnitude group mean, interpatient, interinstitution, and random error, respectively. On multivariable analysis, there were no significant differences in mean vector magnitude by age, gender, performance status, target location, extent of resection, chemotherapy, or steroid or anesthesia use. Providers rated >99% of images as adequate or better for target localization.

Conclusions: A lower-dose cone-beam computed tomography protocol demonstrated table shift vector magnitude that approximate clinical target volume/planning target volume expansions used in central nervous system radiotherapy. There were no significant clinical predictors of setup accuracy identified, supporting use of this lower-dose cone-beam computed tomography protocol across a diverse pediatric population with brain tumors.
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http://dx.doi.org/10.1177/1533033820920650DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7225835PMC
November 2020

Hospitalization and definitive radiotherapy in lung cancer: incidence, risk factors and survival impact.

BMC Cancer 2020 Apr 19;20(1):334. Epub 2020 Apr 19.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, 300 Mason Lord Drive, Baltimore, MD, 21224, USA.

Background: Unplanned hospitalization during cancer treatment is costly, can disrupt treatment, and affect patient quality of life. However, incidence and risks factors for hospitalization during lung cancer radiotherapy are not well characterized.

Methods: Patients treated with definitive intent radiation (≥45 Gy) for lung cancer between 2008 and 2018 at a tertiary academic institution were identified. In addition to patient, tumor, and treatment related characteristics, specific baseline frailty markers (Charlson comorbidity index, ECOG, patient reported weight loss, BMI, hemoglobin, creatinine, albumin) were recorded. All cancer-related hospitalizations during or within 30 days of completing radiation were identified. Associations between baseline variables and any hospitalization, number of hospitalizations, and overall survival were identified using multivariable linear regression and multivariable Cox proportional-hazards models, respectively.

Results: Of 270 patients included: median age was 66.6 years (31-88), 50.4% of patients were male (n = 136), 62% were Caucasian (n = 168). Cancer-related hospitalization incidence was 17% (n = 47), of which 21% of patients hospitalized (n = 10/47) had > 1 hospitalization. On multivariable analysis, each 1 g/dL baseline drop in albumin was associated with a 2.4 times higher risk of any hospitalization (95% confidence interval (CI) 1.2-5.0, P = 0.01), and baseline hemoglobin ≤10 was associated with, on average, 2.7 more hospitalizations than having pre-treatment hemoglobin > 10 (95% CI 1.3-5.4, P = 0.01). After controlling for baseline variables, cancer-related hospitalization was associated with 1.8 times increased risk of all-cause death (95% CI: 1.02-3.1, P = 0.04).

Conclusions: Our data show baseline factors can predict those who may be at increased risk for hospitalization, which was independently associated with increased mortality. Taken together, these data support the need for developing further studies aimed at early and aggressive interventions to decrease hospitalizations during treatment.
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http://dx.doi.org/10.1186/s12885-020-06843-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7169027PMC
April 2020

Spatial Radiation Dose Influence on Xerostomia Recovery and Its Comparison to Acute Incidence in Patients With Head and Neck Cancer.

Adv Radiat Oncol 2020 Mar-Apr;5(2):221-230. Epub 2019 Aug 31.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Purpose: Radiation-induced xerostomia is one of the most prevalent symptoms during and after head and neck cancer radiation therapy (RT). We aimed to discover the spatial radiation dose-based (voxel dose) importance pattern in the major salivary glands in relation to the recovery of xerostomia 18 months after RT, and to compare the recovery voxel dose importance pattern to the acute incidence (injury) pattern.

Methods And Materials: This study included all patients within our database with xerostomia outcomes after completion of curative intensity modulated RT. Common Terminology Criteria for Adverse Events xerostomia grade was used to define recovered versus nonrecovered group at baseline, between end of treatment and 18 months post-RT, and beyond 18 months, respectively. Ridge logistic regression was performed to predict the probability of xerostomia recovery. Voxel doses within geometrically defined parotid glands (PG) and submandibular glands (SMG), demographic characteristics, and clinical factors were included in the algorithm. We plotted the normalized learned weights on the 3-dimensional PG and SMG structures to visualize the voxel dose importance for predicting xerostomia recovery.

Results: A total of 146 head and neck cancer patients from 2008 to 2016 were identified. The superior region of the ipsilateral and contralateral PG was the most influencial for xerostomia recovery. The area under the receiver operating characteristic curve evaluated using 10-fold cross-validation for ridge logistic regression was 0.68 ± 0.07. Compared with injury, the recovery voxel dose importance pattern was more symmetrical and was influenced by lower dose voxels.

Conclusions: The superior portion of the 2 PGs (low dose region) are the most influential on xerostomia recovery and seem to be equal in their contribution. The dissimilarity of the influence pattern between injury and recovery suggests different underlying mechanisms. The importance pattern identified by spatial radiation dose and machine learning methods can improve our understanding of normal tissue toxicities in RT. Further external validation is warranted.
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http://dx.doi.org/10.1016/j.adro.2019.08.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136646PMC
August 2019

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

Phys Med Biol 2020 09 28;65(19):195015. Epub 2020 Sep 28.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21231, United States of America.

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation therapy (IMRT) was measured between one month prior to and one week after the start of IMRT. Weight change between one week and two months after the commencement of IMRT was analyzed, and dichotomized at 5% WL. Each patient had a planning CT and contours of gross tumor volume (GTV) and esophagus (ESO). A total of 355 features including clinical parameter (CP), GTV and ESO (GTV&ESO) dose-volume histogram (DVH), GTV radiomics, and GTV&ESO dosiomics features were extracted. R&D features were categorized as first- (L1), second- (L2), higher-order (L3) statistics, and three combined groups, L1 + L2, L2 + L3 and L1 + L2 + L3. Multi-view texture analysis was performed to identify optimal R&D input features. In the training set (194 earlier patients), feature selection was performed using Boruta algorithm followed by collinearity removal based on variance inflation factor. Machine-learning models were developed using Laplacian kernel support vector machine (lpSVM), deep neural network (DNN) and their averaged ensemble classifiers. Prediction performance was tested on an independent test set (194 more recent patients), and compared among seven different input conditions: CP-only, DVH-only, R&D-only, DVH + CP, R&D + CP, R&D + DVH and R&D + DVH + CP. Combined GTV L1 + L2 + L3 radiomics and GTV&ESO L3 dosiomics were identified as optimal input features, which achieved the best performance with an ensemble classifier (AUC = 0.710), having statistically significantly higher predictability compared with DVH and/or CP features (p < 0.05). When this performance was compared to that with full R&D-only features which reflect traditional single-view data, there was a statistically significant difference (p < 0.05). Using optimized multi-view R&D input features is beneficial for predicting early WL in lung cancer radiotherapy, leading to improved performance compared to using conventional DVH and/or CP features.
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http://dx.doi.org/10.1088/1361-6560/ab8531DOI Listing
September 2020

Acute toxicity outcomes and dosimetric implications from incidental irradiation of adjacent tissues in tangent field hypofractionated breast radiotherapy.

Rep Pract Oncol Radiother 2020 May-Jun;25(3):345-350. Epub 2020 Feb 21.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA.

Purpose: Adjacent tissues-in-beam (TIB) may receive substantial incidental doses within standard tangent fields during hypofractioned whole breast irradiation (HF-WBI). To characterize the impact of dose to TIB, we analyzed dosimetric parameters of TIB and associated acute toxicity.

Materials And Methods: Plans prescribed to 40.5 Gy/15 fractions from 4/2016-1/2018 were evaluated. Structures of interest were contoured: (1) TIB: all tissues encompassed by plan 30% isodose lines, (2) breast, (3) non-breast TIB (nTIB): TIB minus contoured breast. Volumes of TIB, breast, and nTIB receiving 100%-107% of prescription dose (V100-V107) were calculated. Twelve patient- and physician-reported acute toxicities were prospectively collected weekly. Correlations between volumetric and dosimetric parameters were assessed. Uni- and multivariable logistic regressions evaluated toxicity grade changes as a function of TIB, breast, and nTIB V100-V107 (in cm).

Results: We evaluated 137 plans. Breast volume was positively correlated with nTIB and nTIB V100 (rho = 0.52, rho = 0.30, respectively, both p < 0.001). V107 > 2 cm were noted in 14% of breast and 21% of nTIB volumes. On multivariable analyses, increasing breast and nTIB V100 significantly raised odds of grade 2+ dermatitis and burning/twinging pain, respectively; increasing nTIB V105 elevated odds of hyperpigmentation and burning pain; and increasing nTIB V107 raised odds of burning pain. Threshold volumes for >6-fold odds of developing burning pain were TIB V105 > 100 cm and V107 > 5 cm.

Conclusions: For HF-WBI, doses to nTIB over the prescription predicted acute toxicities independent of breast doses. These data support inclusion of TIB as a region of interest in treatment planning and protocol design.
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http://dx.doi.org/10.1016/j.rpor.2020.02.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083790PMC
February 2020

Exploring the Relationship of Radiation Dose Exposed to the Length of Esophagus and Weight Loss in Patients with Lung Cancer.

Pract Radiat Oncol 2020 Jul - Aug;10(4):255-264. Epub 2020 Mar 19.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Purpose: We investigate whether esophageal dose-length parameters (L) can robustly predict significant weight loss-≥5% weight loss during radiation therapy (RT) compared with the weight before RT-in patients with lung cancer treated with definitive intent.

Methods And Materials: Patients with lung cancer treated with conventionally fractionated RT between 2010 and 2018 were retrospectively identified. L and L, the length of full- and partial-circumferential esophagus receiving greater than a threshold dose in Gy, respectively, were created. Multivariate logistic regression examined the associations between individual L and weight loss after adjusting for clinical parameters and correcting for multiple comparisons. Ridge logistic regression examined the relative importance of L compared with dose-volume (V), mean dose (D), and clinical parameters in determining weight loss. Univariate logistic regression examined the unadjusted probability of weight loss for important L parameters.

Results: Among the 214 patients identified, median age was 66.9 years (range, 31.5-88.9 years), 50.5% (n = 108) were male, 68.2% (n = 146) had stage III lung cancer, median RT dose was 63 Gy (range, 60-66 Gy), and 88.3% (n = 189) received concurrent chemotherapy. Esophagus lengths receiving high full-circumferential (L-L) and high partial-circumferential doses (L) were associated with significant weight loss (P ≤ .05). L and L reached near significance (P = .06 and .053, respectively). L > L > L were the most important dose parameters in determining weight loss compared with other L, V, and D parameters.

Conclusions: Esophageal L parameters are an efficient way of interpreting complex dose parameters in relation to weight loss toxicity among patients with lung cancer receiving definitive RT.
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http://dx.doi.org/10.1016/j.prro.2020.03.002DOI Listing
March 2021

A Multidisciplinary Consensus Recommendation on a Synoptic Radiation Treatment Summary: A Commission on Cancer Workgroup Report.

Pract Radiat Oncol 2020 Nov - Dec;10(6):389-401. Epub 2020 Jan 24.

Onco Inc, Wall Township, New Jersey; Salem Health Radiation Oncology, Salem, Oregon.

Purpose: The radiation treatment summary provides a clinical and technical overview of a patient's full course of radiation therapy. Despite its importance to multiple stakeholders, there is no widely followed radiation treatment summary template.

Methods And Materials: The Commission on Cancer convened a multistakeholder workgroup to develop a synoptic radiation treatment summary template. The workgroup included individuals with expertise in radiation, medical and surgical oncology, medical physics, oncology informatics, cancer registry, electronic medical record systems, treatment planning systems, and registry information systems. The workgroup iterated a template until consensus was achieved.

Results: The consensus radiation treatment summary template is divided into 3 sections that allows for a mix of structured and free text. The first section, "Radiation Course Summary," is meant to provide information that is of broad interest and in a manner that is potentially accessible to patients, their families, and nononcology-trained care team members. The second section, "Anatomic Target Summary," provides information that is potentially useful to oncology-trained care team members who will be primarily interested in which anatomies were irradiated, by what modality, and to what cumulative dose. The third section, "Delivered Prescriptions," summarizes technical information that is primarily of interest and accessible to radiation oncology-trained clinicians, registrars, and researchers.

Conclusions: We have proposed a consensus template with 3 sections to meet the needs of a diverse set of consumers. We recommend that providers, professional societies, and accreditation bodies with interest in the radiation treatment summary continue collaborative efforts to test, iterate, and drive adoption of a synoptic template.
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http://dx.doi.org/10.1016/j.prro.2020.01.002DOI Listing
January 2020

Improvements in Physician Clinical Workflow Measures After Implementation of a Dashboard Program.

Pract Radiat Oncol 2020 May - Jun;10(3):151-157. Epub 2019 Dec 5.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Hospital, Baltimore, Maryland. Electronic address:

Purpose: To determine whether a combination of data-driven, personalized feedback and implementation of a graduated, sequential intervention model improved key measures of physician workflow and quality in radiation treatment planning.

Methods And Materials: All radiation oncologists across 3 facilities at a single academic institution were prospectively evaluated on 5 predefined metrics of timeliness and accuracy in the treatment-planning process using a web-based institutional data repository and an institutional incident learning system. The study period encompassed 10 quarters from 2014 to 2016, with 2013 serving as a retrospective baseline. Physicians received quarterly individualized reports of their compliance metrics (a practice labeled the Physician Dashboard), and administrative interventions were initiated if >20% noncompliance with any metric was exceeded within a quarter. Consecutive quarters of noncompliance resulted in escalating interventions, including progress meetings with department leadership, and culminated in financial penalties. Rates of noncompliance were compared before and after implementation of this model.

Results: Three thousand six hundred sixty pre-Dashboard and 9497 post-Dashboard simulations were analyzed. After Dashboard implementation, significant reductions were observed in the rates of simulation orders requiring signature by a covering physician (14.1% vs 7.4%, P < .001), and the submission of plan contours ≥1 day (43.1% vs 23.1%, P < .001) or ≥2 days (30.8% vs 18.3%, P = .002) after the due date. There was some decrease in rates of inaccurate or incomplete plan submissions (6.2% vs 3.9%, P = .08). Seven of the 12 physicians received at least 1 intervention, with only 2 receiving all levels of intervention.

Conclusions: Regular assessment and targeted feedback using the Physician Dashboard significantly improved radiation oncologist compliance with clinically meaningful treatment planning responsibilities at a high-volume academic center.
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http://dx.doi.org/10.1016/j.prro.2019.11.014DOI Listing
December 2020

Frequency of Complicated Symptomatic Bone Metastasis Over a Breadth of Operational Definitions.

Int J Radiat Oncol Biol Phys 2020 03 2;106(4):800-810. Epub 2019 Dec 2.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Purpose: Numerous randomized trials have demonstrated noninferiority of single- versus multiple-fraction palliative radiation therapy (RT) in the management of uncomplicated bone metastases; yet there is neither a clear definition of what constitutes a complicated lesion, nor substantial data regarding the prevalence of such complicating features in clinical practice. Thus, we identify a range of evidence-based operational definitions of complicated symptomatic bone metastases and characterize the frequency of such complicating features at a high-volume, tertiary care center.

Methods And Materials: A retrospective review of patients seen in consultation for symptomatic bone metastases between March 1, 2007, and July 31, 2013, at Johns Hopkins Hospital identified patient and disease characteristics. Descriptive statistics characterized the frequency of the following complicating features: prior RT, prior surgery, neuraxis compromise, pathologic fracture, and soft tissue component at the symptomatic site. A range of definitions for complicated bone metastases was evaluated based on combinations of these features. Uni- and multivariable logistic regressions evaluated the odds of complicated bone metastases as a function of site of primary cancer and of the symptomatic target lesion.

Results: A total of 686 symptomatic bone metastases in 401 patients were evaluated. Percent of target sites complicated by prior RT was 4.4%, prior surgery was 8.9%, pathologic fracture was 20.6%, neuraxis compromise was 52.0% among spine and medial pelvis sites, and soft tissue component was 38.6%. More than 96 possible definitions of complicated bone metastases were identified. The presence of such complicated lesions ranged from 2.3% to 67.3%, depending on the operational definition used. Odds of a complicated lesion were significantly higher for spine sites and select nonbreast histologies.

Conclusions: In this retrospective study, we found complicated symptomatic bone metastases may be present in up to two-thirds of patients. Literature review also demonstrates no clear standard definition of complicated bone metastases, potentially explaining underutilization of single-fraction palliative RT in this setting.
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http://dx.doi.org/10.1016/j.ijrobp.2019.11.033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954524PMC
March 2020

ASTRO Journals' Data Sharing Policy and Recommended Best Practices.

Adv Radiat Oncol 2019 Oct-Dec;4(4):551-558. Epub 2019 Aug 22.

Maastricht University Medical Center, Maastricht, Netherlands.

Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed.
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http://dx.doi.org/10.1016/j.adro.2019.08.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817515PMC
August 2019

Use of Big Data for Quality Assurance in Radiation Therapy.

Semin Radiat Oncol 2019 10;29(4):326-332

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD.

The application of big data to the quality assurance of radiation therapy is multifaceted. Big data can be used to detect anomalies and suboptimal quality metrics through both statistical means and more advanced machine learning and artificial intelligence. The application of these methods to clinical practice is discussed through examples of guideline adherence, contour integrity, treatment delivery mechanics, and treatment plan quality. The ultimate goal is to apply big data methods to direct measures of patient outcomes for care quality. The era of big data and machine learning is maturing and the implementation for quality assurance promises to improve the quality of care for patients.
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http://dx.doi.org/10.1016/j.semradonc.2019.05.006DOI Listing
October 2019

Analysis of Spatial Dose-Volume Relationships and Decline in Sexual Function Following Permanent Brachytherapy for Prostate Cancer.

Urology 2020 Jan 24;135:111-116. Epub 2019 Aug 24.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Hospital, Baltimore, MD. Electronic address:

Objective: To explore relationships between dose to periprostatic anatomic structures and erectile dysfunction (ED) outcomes in an institutional cohort treated with prostate brachytherapy.

Methods: The Sexual Health Inventory for Men (SHIM) instrument was administered for stage cT1-T2 prostate cancer patients treated with Pd-103 brachytherapy over a 10-year interval. Dose volume histograms for regional organs at risk and periprostatic regions were calculated with and without expansions to account for contouring uncertainty. Regression tree analysis clustered patients into ED risk groups.

Results: We identified 115 men treated with definitive prostate brachytherapy who had 2 years of complete follow-up. On univariate analysis, the subapical region (SAR) caudal to prostate was the only defined region with dose volume histograms parameters significant for potency outcomes. Regression tree analysis separated patients into low ED risk (mean 2-year SHIM 20.03), medium ED risk (15.02), and high ED risk (5.54) groups. Among patients with good baseline function (SHIM ≥ 17), a dose ≥72.75 Gy to 20% of the SAR with 1 cm expansion was most predictive for 2-year potency outcome. On multivariate analysis, regression tree risk group remained significant for predicting potency outcomes even after adjustment for baseline SHIM and age.

Conclusion: Dose to the SAR immediately caudal to prostate was predictive for potency outcomes in patients with good baseline function. Minimization of dose to this region may improve potency outcomes following prostate brachytherapy.
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http://dx.doi.org/10.1016/j.urology.2019.08.014DOI Listing
January 2020

Minimum Data Elements for Radiation Oncology: An American Society for Radiation Oncology Consensus Paper.

Pract Radiat Oncol 2019 Nov 21;9(6):395-401. Epub 2019 Aug 21.

Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Purpose: In recent years, the American Society for Radiation Oncology (ASTRO) has received requests for a standard list of data elements from other societies, database architects, Electronic Health Record vendors and, most recently, the pharmaceutical industry. These requests point to a growing interest in capturing radiation oncology data within registries and for quality measurement, interoperability initiatives, and research. Identifying a short and consistent list will lead to improved care coordination, a reduction in data entry by practice staff, and a more complete view of the holistic approach required for cancer treatment.

Methods And Materials: The task force formulated recommendations based on analysis from radiation specific data elements currently in use in registries, accreditation programs, incident learning systems, and electronic health records. The draft manuscript was peer reviewed by 8 reviewers and ASTRO legal counsel and was revised accordingly and posted on the ASTRO website for public comment in April 2019 for 2 weeks. The final document was approved by the ASTRO Board of Directors in June 2019.
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http://dx.doi.org/10.1016/j.prro.2019.07.017DOI Listing
November 2019

Radiation treatment planning with embedded dose escalation.

Radiat Oncol 2019 Aug 14;14(1):145. Epub 2019 Aug 14.

Dept. of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, 401 N Broadway St. Weinberg Suite 1440, Baltimore, MD, 21231, USA.

Background: Heterogeneous target doses are a common by-product from attempts to improve normal tissue sparing in radiosurgery treatment planning. These regions of escalated dose within the target may increase tumor control probability (TCP). Purposely embedding hot spots within tumors during optimization may also increase the TCP. This study discusses and compares five optimization approaches that not only eliminate homogeneity constraints, but also maximize heterogeneity and internal dose escalation.

Methods: Co-planar volumetric modulated arc therapy (VMAT) plans were produced for virtual spherical targets with 2-8 cm diameters, minimum target dose objectives of 25 Gy, and objectives to minimize normal tissue dose. Five other sets of plans were produced with additional target dose objectives: 1) minimum dose-volume histogram (DVH) objective on 10% of the target 2) minimum dose objective on a sub-structure within the target, and 3-5) minimum generalized equivalent uniform dose (gEUD) objectives assuming three different volume-effect parameters. Plans were normalized to provide equivalent maximum OAR dose and were compared in terms of target D0.1 cc, ratio of V12.5 Gy to PTV volume (R50%), monitor units per 5 Gy fraction (MU), and mean multi-leaf collimator (MLC) segment size. All planning approaches were also applied to a clinical patient dataset and compared.

Results: Mean ± standard deviation metrics achievable using the baseline and experimental approaches 1-5) included D0.1 cc: 27.7 ± 0.8, 64.6 ± 10.5, 56.5 ± 10.3, 48.9 ± 5.7, 44.8 ± 5.0, and 37.4 ± 4.5 Gy. R50%: 4.64 ± 3.27, 5.15 ± 2.32, 4.83 ± 2.64, 4.42 ± 1.83, 4.45 ± 1.88, and 4.21 ± 1.75. MU: 795 ± 27, 1988 ± 222, 1766 ± 259, 1612 ± 112, 1524 ± 90, and 1362 ± 146. MLC segment size: 4.7 ± 1.6, 2.3 ± 0.7, 2.6 ± 0.8, 2.7 ± 0.7, 2.7 ± 0.8, and 2.8 ± 0.8 cm.

Conclusions: The DVH-based approach provided the highest embedded doses for all target diameters and patient example with modest increases in R50%, achieved by decreasing MLC segment size while increasing MU. These results suggest that embedding doses > 220% of tumor margin dose is feasible, potentially improving TCP for solid tumors.
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http://dx.doi.org/10.1186/s13014-019-1348-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693221PMC
August 2019

Predicting acute radiation induced xerostomia in head and neck Cancer using MR and CT Radiomics of parotid and submandibular glands.

Radiat Oncol 2019 Jul 29;14(1):131. Epub 2019 Jul 29.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, 401 North Broadway, Suite 1440, Baltimore, MD, 21287-5678, USA.

Purpose: To analyze baseline CT/MR-based image features of salivary glands to predict radiation-induced xerostomia 3-months after head-and-neck cancer (HNC) radiotherapy.

Methods: A retrospective analysis was performed on 266 HNC patients who were treated using radiotherapy at our institution between 2009 and 2018. CT and T1 post-contrast MR images along with NCI-CTCAE xerostomia grade (3-month follow-up) were prospectively collected at our institution. CT and MR images were registered on which parotid/submandibular glands were contoured. Image features were extracted for ipsilateral/contralateral parotid and submandibular glands relative to the location of the primary tumor. Dose-volume-histogram (DVH) parameters were also acquired. Features were pre-selected based on Spearman correlation before modelling by examining the correlation with xerostomia (p < 0.05). A shrinkage regression analysis of the pre-selected features was performed using LASSO. The internal validity of the variable selection was estimated by repeating the entire variable selection procedure using a leave-one-out-cross-validation. The most frequently selected variables were considered in the final model. A generalized linear regression with repeated ten-fold cross-validation was developed to predict radiation-induced xerostomia at 3-months after radiotherapy. This model was tested in an independent dataset (n = 50) of patients who were treated at the same institution in 2017-2018. We compared the prediction performances under eight conditions (DVH-only, CT-only, MR-only, CT + MR, DVH + CT, DVH + CT + MR, Clinical+CT + MR, and Clinical+DVH + CT + MR) using the area under the receiver operating characteristic curve (ROC-AUC).

Results: Among extracted features, 7 CT, 5 MR, and 2 DVH features were selected. The internal cohort (n = 216) ROC-AUC values for DVH, CT, MR, and Clinical+DVH + CT + MR features were 0.73 ± 0.01, 0.69 ± 0.01, 0.70 ± 0.01, and 0.79 ± 0.01, respectively. The validation cohort (n = 50) ROC-AUC values for DVH, CT, MR, and Clinical+DVH + CT + MR features were 0.63, 0.57, 0.66, and 0.68, respectively. The DVH-ROC was not significantly different than the CT-ROC (p = 0.8) or MR-ROC (p = 0.4). However, the CT + MR-ROC was significantly different than the CT-ROC (p = 0.03), but not the Clinical+DVH + CT + MR model (p = 0.5).

Conclusion: Our results suggest that baseline CT and MR image features may reflect baseline salivary gland function and potential risk for radiation injury. The integration of baseline image features into prediction models has the potential to improve xerostomia risk stratification with the ultimate goal of truly personalized HNC radiotherapy.
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http://dx.doi.org/10.1186/s13014-019-1339-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6664784PMC
July 2019

Applying Non-Homogeneous Dose Optimization to Improve Conventionally Fractionated Radiation Plan Quality in Patients with Non-Small Cell Lung Cancer.

Pract Radiat Oncol 2019 Nov 25;9(6):e591-e598. Epub 2019 Jun 25.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Purpose: Nonhomogeneous dose optimization (NHDO) is exploited in stereotactic body radiation therapy (SBRT) to increase dose delivery to the tumor and allow rapid dose falloff to surrounding normal tissues. We investigate changes in plan quality when NHDO is applied to inverse-planned conventionally fractionated radiation therapy (CF-RT) plans in patients with non-small cell lung cancer.

Methods And Materials: Patients with near-central non-small cell lung cancer treated with CF-RT in 2018 at a single institution were identified. CF-RT plans were replanned using NHDO techniques, including normalizing to a lower isodose line, while maintaining clinically acceptable normal tissue constraints and target coverage. Tumor control probabilities were calculated. We compared delivered CF-RT plans using homogenous dose optimization (HDO) versus NHDO using Wilcoxon signed-rank tests. Median values are reported.

Results: Thirteen patients were replanned with NHDO techniques. Planning target volume coverage by the prescription dose was similar (NHDO = 96% vs HDO = 97%, P = .3). All normal-tissue dose constraints were met. NHDO plans were prescribed to a lower-prescription isodose line compared with HDO plans (85% vs 97%, P = .001). NHDO increased mean dose to the planning target volume (73 Gy vs 67 Gy), dose heterogeneity, and dose falloff gradient (P < .03). NHDO decreased mean dose to surrounding lungs, esophagus, and heart (relative reduction of 6%, 14%, and 15%, respectively; P < .05). Other normal tissue objectives improved with NHDO, including total lung V40 and V60, heart V30, and maximum esophageal dose (P < .05). Tumor control probabilities doubled from 31.6% to 65.4% with NHDO (P = .001).

Conclusions: In select patients, NHDO principles used in SBRT optimization can be applied to CF-RT. NHDO results in increased tumor dose, reduction in select organ-at-risk dose objectives, and better maintenance of target coverage and normal-tissue constraints compared with HDO. Our data demonstrate that principles of NHDO used in SBRT can also improve plan quality in CF-RT.
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http://dx.doi.org/10.1016/j.prro.2019.06.010DOI Listing
November 2019

Adoption of an incident learning system in a regionally expanding academic radiation oncology department.

Rep Pract Oncol Radiother 2019 Jul-Aug;24(4):338-343. Epub 2019 Jun 1.

Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, 40 North Broadway, Baltimore, MD 21231, USA.

Aim And Background: We describe a successful implementation of a departmental incident learning system (ILS) across a regionally expanding academic radiation oncology department, dovetailing with a structured integration of the safety and quality program across clinical sites.

Materials And Methods M: Over 6 years between 2011 and 2017, a long-standing departmental ILS was deployed to 4 clinical locations beyond the primary clinical location where it had been established. We queried all events reported to the ILS during this period and analyzed trends in reporting by clinical site. The chi-square test was used to determine whether differences over time in the rate of reporting were statistically significant. We describe a synchronous development of a common safety and quality program over the same period.

Results: There was an overall increase in the number of event reports from each location over the time period from 2011 to 2017. The percentage increase in reported events from the first year of implementation to 2017 was 457% in site 1, 166.7% in site 2, 194.3% in site 3, 1025% in site 4, and 633.3% in site 5, with an overall increase of 677.7%. A statistically significant increase in the rate of reporting was seen from the first year of implementation to 2017 ( < 0.001 for all sites).

Conclusions: We observed significant increases in event reporting over a 6-year period across 5 regional sites within a large academic radiation oncology department, during which time we expanded and enhanced our safety and quality program, including regional integration. Implementing an ILS and structuring a safety and quality program together result in the successful integration of the ILS into existing departmental infrastructure.
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http://dx.doi.org/10.1016/j.rpor.2019.05.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545410PMC
June 2019

Comparison of treatment planning approaches for spatially fractionated irradiation of deep tumors.

J Appl Clin Med Phys 2019 Jun 21;20(6):125-133. Epub 2019 May 21.

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Purpose: The purpose of this work was to compare the dosimetry and delivery times of 3D-conformal (3DCRT)-, volumetric modulated arc therapy (VMAT)-, and tomotherapy-based approaches for spatially fractionated radiation therapy for deep tumor targets.

Methods: Two virtual GRID phantoms were created consisting of 7 "target" cylinders (1-cm diameter) aligned longitudinally along the tumor in a honey-comb pattern, mimicking a conventional GRID block, with 2-cm center-to-center spacing (GRID ) and 3-cm center-to-center spacing (GRID ), all contained within a larger cylinder (8 and 10 cm in diameter for the GRID and GRID , respectively). In a single patient, a GRID structure was created within the gross tumor volume (GTV). Tomotherapy, VMAT (6 MV + 6 MV-flattening-filter-free) and multi-leaf collimator segment 3DCRT (6 MV) plans were created using commercially available software. Two tomotherapy plans were created with field widths (TOMO ) 2.5 cm and (TOMO ) 5 cm. Prescriptions for all plans were set to deliver a mean dose of 15 Gy to the GRID targets in one fraction. The mean dose to the GRID target and the heterogeneity of the dose distribution (peak-to-valley and peak-to-edge dose ratios) inside the GRID target were obtained. The volume of normal tissue receiving 7.5 Gy was determined.

Results: The peak-to-valley ratios for GRID /GRID /Patient were 2.1/2.3/2.8, 1.7/1.5/2.8, 1.7/1.9/2.4, and 1.8/2.0/2.8 for the 3DCRT, VMAT, TOMO , and TOMO plans, respectively. The peak-to-edge ratios for GRID /GRID /Patient were 2.8/3.2/5.4, 2.1/1.8/5.4, 2.0/2.2/3.9, 2.1/2.7/5.2 and for the 3DCRT, VMAT, TOMO , and TOMO plans, respectively. The volume of normal tissue receiving 7.5 Gy was lowest in the TOMO plan (GRID /GRID /Patient = 54 cm /19 cm /10 cm ). The VMAT plans had the lowest delivery times (GRID /GRID /Patient = 17 min/8 min/9 min).

Conclusion: Our results present, for the first time, preliminary evidence comparing IMRT-GRID approaches which result in high-dose "islands" within a target, mimicking what is achieved with a conventional GRID block but without high-dose "tail" regions outside of the target. These approaches differ modestly in their ability to achieve high peak-to-edge ratios and also differ in delivery times.
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http://dx.doi.org/10.1002/acm2.12617DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560243PMC
June 2019