Citations

AbstractBackgroundThis study was aimed at developing and validating a decision‐making tool predictive of overall survival (OS) for patients receiving stereotactic body radiation therapy (SBRT) for spinal metastases.MethodsThree hundred sixty‐one patients at one institution were used for the training set, and 182 at a second institution were used for external validation. Treatments most commonly involved one or three fractions of spine SBRT. Exclusion criteria included proton therapy and benign histologies.ResultsThe final model consisted of the following variables and scores: Spinal Instability Neoplastic Score (SINS) ≥ 6 (1), time from primary diagnosis < 21 months (1), Eastern Cooperative Oncology Group (ECOG) performance status = 1 (1) or ECOG performance status > 1 (2), and >1 organ system involved (1). Each variable was an independent predictor of OS (p < .001), and each 1‐point increase in the score was associated with a hazard ratio of 2.01 (95% confidence interval [CI], 1.79–2.25; p < .0001). The concordance value was 0.75 (95% CI, 0.71–0.78). The scores were discretized into three groups—favorable (score = 0–1), intermediate (score = 2), and poor survival (score = 3–5)—with 2‐year OS rates of 84% (95% CI, 79%–90%), 46% (95% CI, 36%–59%), and 21% (95% CI, 14%–32%), respectively (p < .0001 for each). In the external validation set (182 patients), the score was also predictive of OS (p < .0001). Increasing SINS<zaq;6> was predictive of decreased OS as a continuous variable (p < .0001).ConclusionsThis novel score is proposed as a decision‐making tool to help to optimize patient selection for spine SBRT. SINS may be an independent predictor of OS.

AbstractDespite advancements in local‐regional and systemic therapies, non‐small cell cancer (NSCLC) remains a leading cause of death worldwide. Among those treated with standard‐of‐care modalities, 30–60% experience disease recurrence. Carbon ion radiotherapy (CIRT) is a form of densely ionizing radiotherapy with unique physical and biological advantages over traditional photon and proton modalities. CIRT is expected to have a superior biological impact on tumors, and is believed to be less impacted by the presence of tumor hypoxia or cell cycle state. It also shows highly conformal physical dose deposition due to reduced lateral scattering of the particles, limiting the radiation dose delivered to adjacent organs at risk. To implement CIRT as a viable option in the treatment of NSCLC, technical aspects of treatment delivery – including appropriate beam arrangements, dose calculation algorithms, radiobiological models, and methods of motion management – must be thoroughly investigated. Furthermore, randomized clinical trials comparing CIRT versus traditional radiation modalities must be performed to show the benefits and risks associated with this novel treatment modality. This review discusses the rationale for utilizing CIRT in NSCLC, available clinical data to date, and the potential for future investigations that may pave the path for improving outcomes in those diagnosed with NSCLC.

Abstract PURPOSE Vertebral compression fracture (VCF) is a potential adverse effect following stereotactic body radiation therapy (SBRT) for spinal metastases. In this analysis, we developed and internally validated a risk stratification model for VCF. METHODS From an initial set of 680 treatments, we excluded those with proton therapy, prior surgical intervention, or missing data. The final dataset had 464 treatments in 313 patients. Delineations of VCF and all radiographic components of the spinal instability neoplastic score (SINS) were determined by a radiologist. Recursive partitioning analysis (RPA) was conducted using separate training (70%), internal validation (15%), and test (15%) sets. The log-rank test was used as the criterion for node splitting. RESULTS With a median follow-up of 21 months, we identified 84 VCF (18%), including 65 (77%) de novo and 19 (23%) progressive fractures. There was a median 9 months (IQR: 3 – 21) to VCF. From an initial set of 15 candidate variables, six were identified using the backwards selection method, feature importance testing, and a correlation heatmap. Four were then selected in the highest-fidelity RPA models: epidural tumor extension, lumbar location, gross tumor volume &gt; 10 cc, and SINS &gt; 6. One point was assigned to each variable, and the resulting multivariate Cox model had a concordance of 0.760. Each one point increase in score was associated with increasing rates of VCF. Low-risk lesions (score: 0-1, n=273) had 2-year freedom from VCF of 92%, compared to 80% for intermediate-risk (score: 2, n=99) and 56% (score: 3-4, n=92) for high-risk lesions (p &lt; 0.0001). Cumulative incidence curves with death as a competing risk showed increased VCF with higher scores via Gray’s test (p &lt; 0.001). CONCLUSIONS Our internally-validated model identifies a subgroup of patients with high risk for VCF who may benefit from prophylactic surgical stabilization or vertebroplasty.

e20554 Background: The paradigm for locally advanced non-small cell lung cancer has been markedly altered to include maintenance durvalumab (D) post completion of definitive chemoradiation (CRT) following the publication of the Pacific trial in 2018. The toxicity of this treatment has not been well evaluated in the real-world setting. Methods: We identified 42 patients (pts) with Stage IIB-IIIC NSCLC treated at Mayo Clinic Rochester between 6/1/2018 and 10/1/2020 who received definitive CRT followed by maintenance D. Data were abstracted by retrospective chart review under an IRB approved protocol. Results: Median age was 66 yrs (range 47-90) and 62% were women. Primary lung cancer histology included 19 adenocarcinoma, 20 squamous cell, and 3 adenosquamous. The distribution of stages was: IIB (4/42), IIIA (15/42), IIIB (19/42), IIIC (4/42). Approximately half of patients had PDL1 expression > 25% (20/42). With a median follow up of 12.2 months (calculated from first cycle of D; range 4.2-30.5 months), 14 had completed one year of maintenance D, 16 were receiving ongoing D, and 10 stopped D early with 6/12 discontinuing due to disease progression (4/6 local progression, 2/6 distant progression). Other reasons for discontinuation (5/10) included grade 3 colitis, grade 2 hepatitis, aspergillus lung infection, and flare of autoimmune disorders. One quarter of patients experienced grade 2 radiation pneumonitis (RP; 10/42) with median time to development of RP 78 days from end of CRT and 45 days from start of D. RP was determined by multidisciplinary review of imaging and treatment fields. 17/42 patients developed immune related adverse events (see Table for details). There was minimal overlap between the patients who experienced pneumonitis and immune related toxicity; 2/17 had both pneumonitis and immune related toxicity (hepatitis, thyroiditis). Conclusions: In our early experience with the Pacific regimen, 29% of patients did not complete D due to either toxicity or progression during D administration. Pneumonitis was common (10/42 patients) although there were no grade 3 events. Nearly half of the patients developed an immune-related adverse event. Further analysis is needed to evaluate the real-world toxicity of this treatment as well as oncologic outcomes.[Table: see text]

Objectives We evaluated the outcomes of metastatic pancreatic cancer (MPC) patients who underwent liver metastases (LMs)–directed ablative radiotherapy (RT) and sought to characterize patients with more favorable prognosis. Methods A retrospective analysis of 76 MPC patients who underwent ablative RT (median dose, 50 Gy) to LM at 3 academic centers between 2008 and 2018 was performed. Endpoints were local control (LC), progression-free survival, and overall survival (OS) since RT. Results Median follow-up was 10.9 months. Liver metastases were metachronous in 68%. Before RT, LM was responsive/stable on chemotherapy (CTX) in 36% whereas progressive in 43%. Median carbohydrate antigen 19-9 (CA 19-9) at RT was 334 U/mL. After RT, 32% had ≥6 months of CTX break. Twelve-month outcomes were: LC, 66%; progression-free survival, 7%; and OS, 38%. On multivariable analysis, Eastern Cooperative Oncology Group 2–3 (hazard ratio [HR], 13.49; P < 0.01), progressive LM on CTX (HR, 3.26; P < 0.01), and higher CA 19-9 (log 10 scale; HR, 1.39; P < 0.01) at RT predicted worse OS. Conclusions Ablative RT to LM in setting of MPC may offer LC of systemic disease and thus quality time off CTX. Selected patients with good performance status, stable/responsive LM on CTX, and lower CA 19-9 have more favorable prognosis.

PURPOSE The American Society for Radiation Oncology (ASTRO) produced an evidence-based guideline on radiation therapy (RT) for small-cell lung cancer (SCLC). Because of the relevance of this topic to ASCO membership, ASCO reviewed the guideline, applying a set of procedures and policies used to critically examine guidelines developed by other organizations. METHODS The ASTRO guideline on RT for SCLC was reviewed for developmental rigor by methodologists. Then, an ASCO Expert Panel reviewed the content and the recommendations. RESULTS The ASCO Expert Panel determined that the recommendations from ASTRO guideline on RT for SCLC, published in June 2020, are clear, thorough, and based upon the most relevant scientific evidence. ASCO endorsed ASTRO guideline on RT for SCLC with a few discussion points. RECOMMENDATIONS Recommendations addressed thoracic radiotherapy for limited-stage SCLC, role of stereotactic body radiotherapy in stage I or II node-negative SCLC, prophylactic cranial radiotherapy, and thoracic consolidation for extensive-stage SCLC. Additional information is available at www.asco.org/thoracic-cancer-guidelines .

It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision‐making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.