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Locally advanced lung cancer (LALC) treatment planning is often complex due to challenging tradeoffs related to large targets near organs at risk, making the judgment of plan quality difficult. The purpose of this work was to update and maintain a multi-institutional knowledge-based planning (KBP) model developed by a statewide consortium of academic and community practices for use as a plan quality assurance (QA) tool.Sixty LALC volumetric-modulated arc therapy plans from 2021 were collected from 24 institutions. Plan quality was scored, with high-quality clinical (HQC) plans selected to update a KBP model originally developed in 2017. The model was validated via automated KBP planning, with 20 cases excluded from the model. Differences in dose-volume histogram metrics in the clinical plans, 2017 KBP model plans, and 2022 KBP model plans were compared. Twenty recent clinical cases not meeting consortium quality metrics were replanned with the 2022 model to investigate potential plan quality improvements.Forty-seven plans were included in the final KBP model. Compared with the clinical plans, the 2022 model validation plans improved 60%, 65%, and 65% of the lung V20Gy, mean heart dose, and spinal canal D0.03cc metrics, respectively. The 2022 model showed improvements from the 2017 model in hot spot management at the cost of greater lung doses. Of the 20 recent cases not meeting quality metrics, 40% of the KBP model-replanned cases resulted in acceptable plans, suggesting potential clinical plan improvements.A multi-institutional KBP model was updated using plans from a statewide consortium. Multidisciplinary plan review resulted in HQC model training plans and model validation resulted in acceptable quality plans. The model proved to be effective at identifying potential plan quality improvements. Work is ongoing to develop web-based training plan review tools and vendor-agnostic platforms to provide the model as a QA tool statewide.

BackgroundUterine clear cell and serous carcinomas have a high propensity for locoregional and distant spread, tend to be more advanced at presentation, and carry a higher risk of recurrence and death than endometrioid cancers. Limited prospective data exist to guide evidence-based management of these rare malignancies.ObjectiveThe American Radium Society sought to summarize evidence-based guidelines developed by a multidisciplinary expert panel that help to guide the management of uterine clear cell and serous carcinomas.MethodsThe American Radium Society Appropriate Use Criteria presented in this manuscript were developed by a multidisciplinary expert panel using an extensive analysis of current published literature from peer-reviewed journals. A well-established methodology (modified Delphi) was used to rate the appropriate use of diagnostic and therapeutic procedures for the management of uterine clear cell and serous carcinomas.ResultsThe primary treatment for non-metastatic uterine clear cell and serous carcinomas is complete surgical staging, with total hysterectomy, salpingo-oophorectomy, omentectomy, and lymph node staging. Even in early-stage disease, patients with uterine clear cell and serous carcinomas have a worse prognosis than those with type I endometrial cancers, warranting consideration for adjuvant therapy regardless of the stage. Given the aggressive nature of these malignancies, and until further research determines the most appropriate adjuvant therapy, it may be reasonable to counsel patients about combined-modality treatment with systemic chemotherapy and radiotherapy.ConclusionPatients diagnosed with uterine clear cell and serous carcinomas should undergo complete surgical staging. Multimodal adjuvant therapies should be considered in the treatment of both early-stage and advanced-stage disease. Further prospective studies or multi-institutional retrospective studies are warranted to determine optimal sequencing of therapy and appropriate management of patients based on their unique risk factors. Long-term surveillance is indicated due to the high risk of locoregional and distant recurrence.

Introduction: Little data have been reported about the patient experience during curative radiotherapy for lung cancer in routine clinical practice, or how this relates to treatment toxicity reported by clinicians. The purpose of this study was to compare clinician-reported adverse events (AEs) with patient-reported outcomes (PROs) including both specific symptoms/side effects as well as overall quality of life (QOL) during and after definitive radiotherapy (RT) for locally advanced lung cancer (LALC) in a large statewide cohort. Methods and Materials: Patient-reported outcomes (PROs) were prospectively collected from patients treated with definitive radiotherapy for LALC at 24 institutions within the XXXX Radiation Oncology Quality Consortium between 2012-2018 using the Functional Assessment of Cancer Therapy Trial Outcome Index (FACT-TOI). Physicians prospectively recorded adverse events (AEs) using CTCAE version 4.0. Patient-reported quality of life (QOL) changes from baseline were assessed during and after radiotherapy using the FACT-TOI. Spearman correlation coefficients were calculated for AEs and similar PROs, and multivariable analysis was used to assess associations with QOL. Results: 1361 patients were included and 53% of respondents reported clinically meaningful declines in QOL at the end of RT. Correlation between clinician-reported esophagitis and patient-reported trouble swallowing was moderate (R=0.67) while correlations between clinician-reported pneumonitis and patient-reported shortness of breath (R=0.13) and cough (R=0.09) were weak. Clinician-reported AEs were significantly associated with clinically meaningful declines inpatient-reported QOL, with R=-0.46 for a summary AE-score. QOL was more strongly associated with fatigue (R=-0.41) than lung-specific AEs. Conclusions: AEs are associated with clinically meaningful declines in QOL during and after RT for LALC, but associations between AEs and QOL are only modest. This highlights the importance of PRO data, and future research should assess whether earlier detection of PRO changes could allow for interventions that reduce the frequency of treatment-related clinically meaningful declines in QOL.

To evaluate the impact of prophylactic paraortic lymph node (PALN) radiation therapy (RT) on clinical outcomes in patients with International Federation of Obstetrics and Gynecology 2018 stage IIIC1 endometrial cancer (EC).A multi-institutional retrospective study included patients with International Federation of Obstetrics and Gynecology 2018 stage IIIC1 EC lymph node assessment, status postsurgical staging, followed by adjuvant chemotherapy and RT using various sequencing regimens. Overall survival (OS) and recurrence-free survival (RFS) rates were estimated by the Kaplan-Meier method. Univariable and multivariable analysis were performed by Cox proportional hazard models for RFS/OS. In addition, propensity score matching was used to estimate the effect of the radiation field extent on survival outcomes.A total of 378 patients were included, with a median follow-up of 45.8 months. Pelvic RT was delivered to 286 patients, and 92 patients received pelvic and PALN RT. The estimated OS and RFS rates at 5 years for the entire cohort were 80% and 69%, respectively. There was no difference in the 5-year OS (77% vs 87%, P = .47) and RFS rates (67% vs 70%, P = .78) between patients treated with pelvic RT and those treated with pelvic and prophylactic PALN RT, respectively. After propensity score matching, the estimated hazard ratios (HRs) of prophylactic PALN RT versus pelvic RT were 1.50 (95% confidence interval, 0.71-3.19; P = .28) for OS and 1.24 (95% confidence interval, 0.64-2.42; P = .51) for RFS, suggesting that prophylactic PALN RT does not improve survival outcomes. Distant recurrence was the most common site of first recurrence, and the extent of RT field was not associated with the site of first recurrence (P = .79).Prophylactic PALN RT was not significantly associated with improved survival outcomes in stage IIIC1 EC. Distant metastasis remains the most common site of failure despite routine use of systemic chemotherapy. New therapeutic approaches are necessary to optimize the outcomes for women with stage IIIC1 EC.

This review article highlights the treatment paradigms for early-stage endometrial cancer with a focus on the role of external beam radiation therapy. We aim for this review to serve as an introductory resource for gynecological oncologists, radiation oncologists, medical oncologists, and other practitioners to understand the treatments for this disease. The main treatment of endometrial cancer is surgical resection with total hysterectomy and bilateral salpingo-oophorectomy. The benefit of adjuvant radiation after surgery is primarily to prevent local recurrence. Patients with low risk of recurrence can be observed post-operatively. Vaginal cuff brachytherapy, which has been shown to be equally effective as pelvic radiation with fewer side effects, is typically recommended for high–intermediate risk patients (with characteristics such as lymphovascular space invasion, high grade, or significant myometrial invasion). In the adjuvant setting, pelvic radiation therapy is reserved for patients who have deeply invasive stage I grade 2 or 3 disease, stage II disease, and non-endometrioid histologies. In patients who are not medically operable, definitive treatment consists of brachytherapy±pelvic external beam radiation therapy. We have highlighted the main acute and long-term side effects of pelvic radiation as well as recommendations for symptom management and summarized promising evidence showing improved rates of toxicities with more conformal radiation techniques.

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Purpose:Carcinomas originate from epithelial tissues, which have apical (luminal) and basal orientations. The degree of luminal versus basal differentiation in cancer has been shown to be biologically important in some carcinomas and impacts treatment response.Experimental Design:Although prior studies have focused on individual cancer types, we used a modified clinical-grade classifier (PAM50) to subtype 8,764 tumors across 22 different carcinomas into luminal A, luminal B, and basal-like tumors.Results:We found that all epithelial tumors demonstrated similar gene expression–based luminal/basal subtypes. As expected, basal-like tumors were associated with increased expression of the basal markers KRT5/6 and KRT14, and luminal-like tumors were associated with increased expression of the luminal markers KRT20. Luminal A tumors consistently had improved outcomes compared with basal across many tumor types, with luminal B tumors falling between the two. Basal tumors had the highest rates of TP53 and RB1 mutations and copy number loss. Luminal breast, cervical, ovarian, and endometrial tumors had increased ESR1 expression, and luminal prostate, breast, cervical, and bladder tumors had increased androgen receptor (AR) expression. Furthermore, luminal B tumors had the highest rates of AR and ESR1 mutations and had increased sensitivity in vitro to bicalutamide and tamoxifen. Luminal B tumors were more sensitive to gemcitabine, and basal tumors were more sensitive to docetaxel.Conclusions:This first pan-carcinoma luminal/basal subtyping across epithelial tumors reveals global similarities across carcinomas in the transcriptome, genome, clinical outcomes, and drug sensitivity, emphasizing the biological and translational importance of these luminal versus basal subtypes.

Purpose:We recently reported that indoleamine 2, 3-dioxygenase (IDO) activity is significantly correlated with more distant metastasis and worse survival. The present study examined whether radiotherapy (RT) dose fractionation correlates with IDO-mediated immune activity in patients with early-stage NSCLC.Methods: Patients with newly diagnosed stage I-II NSCLC treated with either conventionally fractionated 3-dimensional conformal radiotherapy (3DCRT) or stereotactic body radiotherapy (SBRT) were analyzed. Levels of two key molecules associated with the IDO immune checkpoint, serum kynurenine and the kynurenine:tryptophan ratio (K:T ratio), were measured at pre-RT, during-RT, and 3-month post-RT. The relationship between disease control outcomes [overall survival (OS), progression free survival, and local/regional/distant failure rates] and absolute levels of these markers, as well as dynamic changes in their levels during RT, was studied.Results:Fifty-six patients (SBRT = 28, 3DCRT = 28) with early-stage NSCLC were studied. In all patients, higher kynurenine post-RT was significantly associated with worse OS ([HR, 1.25; 95% confidence interval (CI), 1.01–1.55; P = 0.044). No statistically significant differences in absolute kynurenine levels or the K:T ratio were observed in patients treated with 3DCRT or SBRT at any of the three time points. However, the absolute kynurenine levels rose significantly more post-RT in the 3DCRT patients with a median increase 0.721 ng/mL, compared to that of SBRT patients (0.115 ng/mL); P = 0.022.Conclusions:This study validated that elevated IDO activity correlated with worse survival outcomes in patients with early-stage NSCLC treated with definitive RT. Hypofractionated SBRT may have less immunosuppressive effect than 3DCRT, as measured by IDO.

prediction abilities in the previous reports

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Purpose:Radiation pneumonitis is an important adverse event in patients with non–small cell lung cancer (NSCLC) receiving thoracic radiotherapy. However, the risk of radiation pneumonitis grade ≥ 2 (RP2) has not been well predicted. This study hypothesized that inflammatory cytokines or the dynamic changes during radiotherapy can improve predictive accuracy for RP2.Experimental Design:Levels of 30 inflammatory cytokines and clinical information in patients with stages I–III NSCLC treated with radiotherapy were from our prospective studies. Statistical analysis was used to select predictive cytokine candidates and clinical covariates for adjustment. Machine learning algorithm was used to develop the generalized linear model for predicting risk RP2.Results:A total of 131 patients were eligible and 17 (13.0%) developed RP2. IL8 and CCL2 had significantly (Bonferroni) lower expression levels in patients with RP2 than without RP2. But none of the changes in cytokine levels during radiotherapy was significantly associated with RP2. The final predictive GLM model for RP2 was established, including IL8 and CCL2 at baseline level and two clinical variables. Nomogram was constructed based on the GLM model. The model's predicting ability was validated in the completely independent test set (AUC = 0.863, accuracy = 80.0%, sensitivity = 100%, specificity = 76.5%).Conclusions:By machine learning, this study has developed and validated a comprehensive model integrating inflammatory cytokines with clinical variables to predict RP2 before radiotherapy that provides an opportunity to guide clinicians.

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Table S1 and Figure S1

Detail of Prospective Clinical Trials.

As portable chest X-rays are an efficient means of triaging emergent cases, their increased use has raised the question as to whether imaging carries additional prognostic utility for survival among patients with COVID-19. This study assessed the importance of known risk factors on in-hospital mortality and to investigate the predictive utility of radiomic texture features using various machine learning approaches. We detected incremental improvements in survival prognostication utilizing texture features derived from emergent chest X-rays, particularly among older patients or those with higher comorbidity burden. Important features included age, oxygen saturation, blood pressure, and certain comorbid conditions, as well as image features related to the intensity and variability of the pixel distribution. Thus, widely available chest X-rays, in conjunction with clinical information, may be predictive of survival outcomes of patients with COVID-19, especially older, sicker patients, and can aid in disease management by providing additional information.

BackgroundInvolvement of many variables, uncertainty in treatment response, and inter-patient heterogeneity challenge objective decision-making in dynamic treatment regime (DTR) in oncology. Advanced machine learning analytics in conjunction with information-rich dense multi-omics data have the ability to overcome such challenges. We have developed a comprehensive artificial intelligence (AI)-based optimal decision-making framework for assisting oncologists in DTR. In this work, we demonstrate the proposed framework to Knowledge Based Response-Adaptive Radiotherapy (KBR-ART) applications by developing an interactive software tool entitled Adaptive Radiotherapy Clinical Decision Support (ARCliDS).MethodsARCliDS is composed of two main components: Artificial RT Environment (ARTE) and Optimal Decision Maker (ODM). ARTE is designed as a Markov decision process and modeled via supervised learning. Given a patient’s pre- and during-treatment information, ARTE can estimate treatment outcomes for a selected daily dosage value (radiation fraction size). ODM is formulated using reinforcement learning and is trained on ARTE. ODM can recommend optimal daily dosage adjustments to maximize the tumor local control probability and minimize the side effects. Graph Neural Network (GNN) is applied to exploit the inter-feature relationships for improved modeling performance and a novel double GNN architecture is designed to avoid unphysical treatment response. Datasets of size 117 and 292 were available from two clinical trials on adaptive RT in non-small cell lung cancer (NSCLC) patients and adaptive stereotactic body RT (SBRT) in hepatocellular carcinoma (HCC) patients, respectively. For training and validation, dense data with 297 features were available for 67 NSCLC patients and 110 features for 71 HCC patients. To increase the sample size for ODM training, we applied Generative Adversarial Network to generate 10,000 synthetic patients. The ODM was trained on the synthetic patients and validated on the original dataset.ResultsDouble GNN architecture was able to correct the unphysical dose-response trend and improve ARCliDS recommendation. The average root mean squared difference (RMSD) between ARCliDS recommendation and reported clinical decisions using double GNNs were 0.61 ± 0.03 Gy/frac (mean±sem) for adaptive RT in NSCLC patients and 2.96 ± 0.42 Gy/frac for adaptive SBRT HCC compared to the single GNN’s RMSDs of 0.97 ± 0.12 Gy/frac and 4.75 ± 0.16 Gy/frac, respectively. Overall, For NSCLC and HCC, ARCliDS with double GNNs was able to reproduce 36% and 50% of the good clinical decisions (local control and no side effects) and improve 74% and 30% of the bad clinical decisions, respectively.ConclusionARCliDS is the first web-based software dedicated to assist KBR-ART with multi-omics data. ARCliDS can learn from the reported clinical decisions and facilitate AI-assisted clinical decision-making for improving the outcomes in DTR.

Current radiation therapy (RT) treatment planning relies mainly on pre-defined dose-based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population-based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient-specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity-modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient-specific dose response models into the planning process. In this strategy, we integrate the concept of utility-based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non-small cell lung cancer (NSCLC) patients.We developed a prioritized approach to patient-specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet-dose contributions to regions-of-interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade-off based on individualized dose-response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose-based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3-5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors.The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility-based plans resulted in similar local control estimates with decreased estimated toxicity.The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility-based objective function offers an intuitive, humanized approach to biological optimization in which planning trade-offs are explicitly optimized.

The addition of adjuvant durvalumab improves overall survival in locally advanced nonsmall-cell lung cancer (NSCLC) patients treated with definitive chemoradiation, but the real-world uptake of adjuvant durvalumab is unknown.We identified patients with stage III NSCLC treated with definitive concurrent chemoradiation from January 2018 to October 2020 from a statewide radiation oncology quality consortium, representing a mix of community (n=22 centers) and academic (n=5) across the state of Michigan. Use of adjuvant durvalumab was ascertained at the time of routine 3-month or 6-month follow-up after completion of chemoradiation.Of 421 patients with stage III NSCLC who completed chemoradiation, 322 (76.5%) initiated adjuvant durvalumab. The percentage of patients initiating adjuvant durvalumab increased over time from 66% early in the study period to 92% at the end of the study period. There was substantial heterogeneity by treatment center, ranging from 53% to 90%. In multivariable logistic regression, independent predictors of durvalumab initiation included more recent month (odds ratio [OR]: 1.05 per month, 95% confidence interval [CI]: 1.02-1.08, P=0.003), lower Eastern Cooperative Oncology Group score (OR: 4.02 for ECOG 0 vs. 2+, 95% CI: 1.67-9.64, P=0.002), and a trend toward significance for female sex (OR: 1.66, 95% CI: 0.98-2.82, P=0.06).Adjuvant durvalumab for stage III NSCLC treated with definitive chemoradiation was rapidly and successfully incorporated into clinical care across a range of community and academic settings in the state of Michigan, with over 90% of potentially eligible patients starting durvalumab in more recent months.

Single cycle induction chemotherapy (IC) with platinum and 5-flurouracil (PF) and treatment based on clinical response predicts organ preservation in laryngeal cancer. Other agents offer intriguing alternatives with potentially increased ease of administration, reduced risk for severe toxicities, and increased platinum sensitivity.We report the results of a phase II bioselection trial in advanced resectable laryngeal cancer utilizing an IC regimen of two cycles of platinum plus docetaxel (TP) with a Bcl-2 inhibitor. The primary endpoint was organ preservation rate at 12 weeks post chemoradiation.Fifty-four patients were enrolled. Response to IC was 72%. The organ preservation rate was 59% with a laryngectomy free survival of 46%. Induction related grade ≥3 toxicities were observed in 56% of patients with two grade 5 events.Two cycles of TP IC plus a Bcl-2 inhibitor did not improve laryngeal preservation compared to a single cycle of PF.

8510 Background: Standard therapy for unresectable locally advanced non-small cell lung cancer (LA-NSCLC) is concurrent chemoradiotherapy followed by adjuvant durvalumab. We performed a prospective trial testing sequential pembrolizumab and risk-adapted radiotherapy without chemotherapy for biomarker-selected LA-NSCLC patients. Methods: Patients with stage III NSCLC or unresectable stage II NSCLC, ECOG performance status 0-1, and no contraindications to protocol-specified therapy were eligible for this trial. Subjects with PD-L1 tumor proportion score (TPS) ≥ 50% underwent baseline FDG-PET/CT, received three cycles of induction pembrolizumab (200 mg, every 21 days), underwent restaging FDG-PET/CT, received risk-adapted thoracic radiotherapy (55 Gy delivered to tumors or lymph nodes with metabolic tumor volume exceeding 20 cc and 48 Gy delivered to smaller lesions, all in 20 daily fractions), and then received up to 13 cycles of additional pembrolizumab. The primary study endpoint was one-year progression-free survival (PFS). Here we report response rates following induction pembrolizumab, PFS and overall survival (OS) rates, and adverse event rates (CTCAE v. 4.03). Results: Twenty-five subjects with PD-L1 TPS ≥ 50% from three institutions were enrolled between August 2018 and November 2021. Median age was 71 (interquartile range [IQR] 62 to 77). One subject had stage II disease, 13 had stage IIIA disease, nine had stage IIIB disease, and two had stage IIIC disease. Median PD-L1 TPS was 75% (IQR 60 to 80%). Two subjects (8%) developed disease progression during induction pembrolizumab, and two subjects discontinued pembrolizumab after one infusion due to immune-related adverse events. Using RECIST 1.1 criteria, 12 subjects (48%) exhibited a partial (n = 11) or complete (n = 1) response following induction pembrolizumab on CT. Using PERCIST criteria, 12 subjects (48%) exhibited a partial response following induction pembrolizumab on PET. Four subjects had responses on PET but not on CT, and four had responses on CT but not on PET. With a median follow-up duration of 13 months, the actuarial 1-year PFS rate is 74%, and the actuarial 1-year OS rate is 95%. Grade 3 adverse events have been limited to single cases of anemia, arthritis, diarrhea, esophagitis, and pneumonitis, and no grade 4-5 adverse events have occurred. Exploratory analyses suggest that response to induction pembrolizumab on PET predicts efficacy of this treatment approach, with a 1-year PFS rate of 100% for responders, compared to 61% for non-responders (logrank p = 0.007). Conclusions: Treatment with pembrolizumab and risk-adapted radiotherapy is a promising treatment approach for LA-NSCLC patients with PD-L1 TPS ≥ 50%. Response on PET following induction pembrolizumab may be useful for identifying patients who can be treated successfully without chemotherapy. Clinical trial information: NCT03523702.