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Background: Improved treatment strategies are needed for patients with locally advanced gastric cancer with poor response to neoadjuvant chemotherapy. We aimed to describe patterns of failure for patients with no or partial response (NR, PR) to preoperative chemotherapy. Patients and Methods: We analyzed patients with locally advanced gastric cancer treated from 2008 to 2022 with preoperative chemotherapy followed by surgery with D2 resection. We excluded patients who received radiation. Cumulative incidence of locoregional failure (LRF) and distant metastases (DM) were calculated. For patients with recurrent abdominal disease, hypothetical radiation clinical treatment volumes (CTV) were contoured on postoperative scans and compared with patterns of recurrence. Results: A total of 60 patients were identified. The most used preoperative chemotherapy was FLOT (38.6%), followed by FOLFOX (30%) and ECF/ECX/EOX (23.3%). Four (6.7%), 40 (66.7%), and 9 patients (15%) had a complete pathologic response (CR), PR, and NR to neoadjuvant therapy, respectively. Among patients without a CR, 3-year overall and progression-free survival rates were 62.3% (95% CI 48–76.6%) and 51.3% (95% CI 36.9–65.7%), respectively. Three-year cumulative incidence of LRF and DM were 8.4% (95% CI 0.4–16.4%) and 41.0% (95% CI 26.3–55.4%), respectively. Absolute rates of patients having the first site of recurrence encompassed by a postoperative radiation CTV was 2.0% for patients without a CR and 0% for patients with NR. Conclusions: Patients with locally advanced gastric cancer with less than a CR to chemotherapy have poor outcomes due to high rates of DM. Adjuvant locoregional therapy such as radiation is unlikely to affect survival. [ABSTRACT FROM AUTHOR]

Background: Performing selective esophagectomy for locally advanced squamous cell carcinoma may spare patients morbidity, but delayed surgery may infer higher risks. This study evaluated the impact of length of time between chemoradiation and esophagectomy on perioperative outcomes and long-term survival. Methods: The impact of surgical timing, stratified by surgery performed < 180 and ≥ 180 days from starting radiation, on perioperative outcomes and survival in patients treated with chemoradiation and esophagectomy for cT1N + M0 and cT2–4, any N, M0 squamous cell carcinoma of the mid-distal esophagus in the National Cancer Database (2006–2016) was evaluated with logistic regression, Kaplan–Meier curves, Cox proportional-hazards methods, and propensity-matched analysis. Results: Median time between starting radiation and esophagectomy in 1641 patients was 93 (IQR 81–114) days. Most patients (96.8%, n = 1589) had surgery within 180 days of starting radiation, while 52 patients (3.2%) had delayed surgery. Black race and clinical T stage were associated with delayed surgery. Rates of pathologic upstaging, downstaging, complete response, and positive margins were not significantly different between the groups. Patients with delayed surgery had increased major morbidity as measured by a composite of length of hospital stay, readmission, and 30-day mortality [42.3% (22/52) vs 22.3% (355/1589), p = 0.001]. However, delayed surgery was not associated with a significant difference in survival in both univariate [5-year survival 32.8% (95% CI 21.1–50.7) vs 47.3% (44.7–50.1), p = 0.19] and multivariable analysis [hazard ratio (HR) 1.23 (0.85–1.78), p = 0.26]. Conclusions: Delaying surgery longer than 180 days after starting chemoradiation for esophageal squamous cell carcinoma is associated with worse perioperative outcomes but not long-term survival. [ABSTRACT FROM AUTHOR]

PURPOSE: Older hospitalized cancer patients face high risks of hospital mortality. Improved risk stratification could help identify high-risk patients who may benefit from future interventions, although we lack validated tools to predict in-hospital mortality for patients with cancer. We evaluated the ability of a high-dimensional machine learning prediction model to predict inpatient mortality and compared the performance of this model to existing prediction indices. METHODS: We identified patients with cancer older than 75 years from the National Emergency Department Sample between 2016 and 2018. We constructed a high-dimensional predictive model called Cancer Frailty Assessment Tool (cFAST), which used an extreme gradient boosting algorithm to predict in-hospital mortality. cFAST model inputs included patient demographic, hospital variables, and diagnosis codes. Model performance was assessed with an area under the curve (AUC) from receiver operating characteristic curves, with an AUC of 1.0 indicating perfect prediction. We compared model performance to existing indices including the Modified 5-Item Frailty Index, Charlson comorbidity index, and Hospital Frailty Risk Score. RESULTS: We identified 2,723,330 weighted emergency department visits among older patients with cancer, of whom 144,653 (5.3%) died in the hospital. Our cFAST model included 240 features and demonstrated an AUC of 0.92. Comparator models including the Modified 5-Item Frailty Index, Charlson comorbidity index, and Hospital Frailty Risk Score achieved AUCs of 0.58, 0.62, and 0.71, respectively. Predictive features of the cFAST model included acute conditions (respiratory failure and shock), chronic conditions (lipidemia and hypertension), patient demographics (age and sex), and cancer and treatment characteristics (metastasis and palliative care). CONCLUSION: High-dimensional machine learning models enabled accurate prediction of in-hospital mortality among older patients with cancer, outperforming existing prediction indices. These models show promise in identifying patients at risk of severe adverse outcomes, although additional validation and research studying clinical implementation of these tools is needed. [ABSTRACT FROM AUTHOR]

Background: To test whether nomograms developed by NRG Oncology for oropharyngeal squamous cell carcinoma (OPSCC) patients could be validated in an independent population‐based sample. Methods: The authors tested nomograms for estimating progression‐free survival (PFS) and overall survival (OS) in patients from the Veterans Health Administration with previously untreated locoregionally advanced OPSCC, diagnosed between 2008 and 2017, managed with definitive radiotherapy with or without adjuvant systemic therapy. Covariates were age, performance status, p16 status, T/N category, smoking history, education history, weight loss, marital status, and anemia. We used multiple imputation to handle missing data and performed sensitivity analyses on complete cases. Validation was assessed via Cox proportional hazards models, log‐rank tests, and c‐indexes. Results: A total of 4007 patients met inclusion criteria (658 patients had complete data). Median follow‐up time was 3.20 years, with 967 progression events and 471 noncancer deaths. Each risk score was associated with poorer outcomes per unit increase (PFS score, hazard ratio [HR], 1.42 [1.37‐1.47]; OS score, HR, 1.40 [1.34‐1.45]). By risk score quartile, 2‐year PFS estimates were 89.2%, 78.5%, 65.8%, and 48.3%; OS estimates were 92.6%, 83.6%, 73.9%, and 51.3%, respectively (P <.01 for all comparisons). C‐indices for models of PFS and OS were 0.65 and 0.67, for all patients, respectively (0.69 and 0.73 for complete cases). The nomograms slightly overestimated PFS and OS in the overall cohort but exhibited high agreement in complete cases. Conclusions: NRG nomograms were effective for predicting PFS and OS for patients with OPSCC, supporting their broader applicability in the OPSCC population undergoing definitive radiotherapy. Nomograms, including ones created by the Radiation Therapy Oncology Group (RTOG), can significantly refine prognostication, but previous attempts at external validation have been unsuccessful, possibly related to the handling of missing data. The RTOG nomograms generally performed well for prediction and risk‐stratification, especially in patients without missing data, but slightly overestimated progression‐free survival and overall survival in the overall population. [ABSTRACT FROM AUTHOR]

Background: There is limited research on how the opioid epidemic and consequent risk reduction policies have affected pain management among cancer patients. The purpose of this study was to analyze how the Opioid Safety Initiative (OSI) implemented at the Veterans Health Administration affected opioid prescribing patterns and opioid-related toxicity.Methods: We performed an interrupted time series analysis of 42 064 opioid-naïve patients treated at the Veterans Health Administration for prostate, lung, breast, and colorectal cancer from 2011 to 2016. Segmented regression was used to evaluate the impact of the OSI on the incidence of any new opioid prescriptions, high-risk prescriptions, persistent use, and pain-related emergency department (ED) visits. We compared the cumulative incidence of adverse opioid events including an opioid-related admission or diagnosis of misuse before and after the OSI. All statistical tests were 2-sided.Results: The incidence of new opioid prescriptions was 26.7% (95% confidence interval [CI] = 25.0% to 28.4%) in 2011 and increased to 50.6% (95% CI = 48.3% to 53.0%) by 2013 before OSI implementation (monthly rate of change: +3.3%, 95% CI = 1.3% to 4.2%, P < .001). After the OSI, there was a decrease in the monthly rate of change for new prescriptions (-3.4%, 95% CI = -3.9 to -2.9%, P < .001). The implementation of the OSI was associated with a decrease in the monthly rate of change of concomitant benzodiazepines and opioid prescriptions (-2.5%, 95% CI = -3.2% to -1.8%, P < .001), no statistically significant change in high-dose opioids (-1.2%, 95% CI = -3.2% to 0.9%, P = .26), a decrease in persistent opioid use (-5.7%, 95% CI = -6.8% to -4.7%, P < .001), and an increase in pain-related ED visits (+3.0%, 95% CI = 1.0% to 5.0%, P = .003). The OSI was associated with a decreased incidence of opioid-related admissions (3-year cumulative incidence: 0.9% [95% CI = 0.7% to 1.0%] vs 0.5% [95% CI = 0.4% to 0.6%], P < .001) and no statistically significant change in the incidence of opioid misuse (3-year cumulative incidence: 1.2% [95% CI = 1.0% to 1.3%] vs 1.2% [95% CI = 1.1% to 1.4%], P = .77).Conclusions: The OSI was associated with a relative decline in the rate of new, persistent, and certain high-risk opioid prescribing as well as a slight increase in the rate of pain-related ED visits. Further research on patient-centered outcomes is required to optimize opioid prescribing policies for patients with cancer. [ABSTRACT FROM AUTHOR]

Background: Despite guideline recommendations, utilization of low‐dose computed tomography (LDCT) for lung cancer screening remains low. The driving factors behind these low rates and the real‐world effect of LDCT utilization on lung cancer outcomes remain limited. Methods: We identified patients diagnosed with non‐small cell lung cancer (NSCLC) from 2015 to 2017 within the Veterans Health Administration. Multivariable logistic regression assessed the influence of LDCT screening on stage at diagnosis. Lead time correction using published LDCT lead times was performed. Cancer‐specific mortality (CSM) was evaluated using Fine–Gray regression with non‐cancer death as a competing risk. A lasso machine learning model identified important predictors for receiving LDCT screening. Results: Among 4664 patients, mean age was 67.8 with 58‐month median follow‐up, 95% CI = [7–71], and 118 patients received ≥1 screening LDCT before NSCLC diagnosis. From 2015 to 2017, LDCT screening increased (0.1%–6.6%, mean = 1.3%). Compared with no screening, patients with ≥1 LDCT were more than twice as likely to present with stage I disease at diagnosis (odds ratio [OR] 2.16 [95% CI 1.46–3.20]) and less than half as likely to present with stage IV (OR 0.38 [CI 0.21–0.70]). Screened patients had lower risk of CSM even after adjusting for LDCT lead time (subdistribution hazard ratio 0.60 [CI 0.42–0.85]). The machine learning model achieved an area under curve of 0.87 and identified diagnosis year and region as the most important predictors for receiving LDCT. White, non‐Hispanic patients were more likely to receive LDCT screening, whereas minority, older, female, and unemployed patients were less likely. Conclusions: Utilization of LDCT screening is increasing, although remains low. Consistent with randomized data, LDCT‐screened patients were diagnosed at earlier stages and had lower CSM. LDCT availability appeared to be the main predictor of utilization. Providing access to more patients, including those in diverse racial and socioeconomic groups, should be a priority. [ABSTRACT FROM AUTHOR]

PURPOSE Minority race and lower socioeconomic status are associated with lower rates of opioid prescription and undertreatment of pain in multiple noncancer healthcare settings. It is not known whether these differences in opioid prescribing exist among patients undergoing cancer treatment. METHODS AND MATERIALS This observational cohort study involved 33,872 opioid-naive patients of age ≤ 65 years undergoing definitive cancer treatment. We compared rates of new opioid prescriptions by race or ethnicity and socioeconomic status controlling for differences in baseline patient, cancer, and treatment factors. To evaluate downstream impacts of opioid prescribing and pain management, we also compared rates of persistent opioid use and pain-related emergency department (ED) visits. RESULTS Compared with non-Hispanic White patients, the covariate-adjusted odds of receiving an opioid prescription were 24.9% (95% CI, 16.0 to 33.9, P, .001) lower for non-Hispanic Blacks, 115.0% (84.7 to 150.3, P, .001) higher for Asian-Pacific Islanders, and not statistically different for Hispanics (21.0 to 14.0, P5.06). There was no significant association between race or ethnicity and persistent opioid use or pain-related ED visits. Patients living in a high-poverty area had higher odds (53.9% [25.4 to 88.8, P, .001]) of developing persistent use and having a pain-related ED visit (39.4% [16.4 to 66.9, P, .001]). CONCLUSION For older patients with cancer, rates of opioid prescriptions and pain-related outcomes significantly differed by race and area-level poverty. Non-Hispanic Black patients were associated with a significantly decreased likelihood of receiving an opioid prescription. Patients from high-poverty areas were more likely to develop persistent opioid use and have a pain-related ED visit. [ABSTRACT FROM AUTHOR]

Background: Clinical guidelines recommend that providers risk-stratify patients with cancer before prescribing opioids. Prior research has demonstrated that a simple cancer opioid risk score might help identify to patients with cancer at the time of diagnosis with a high likelihood of long-term posttreatment opioid use. This current project validates this cancer opioid risk score in a generalizable, population-based cohort of elderly cancer survivors.Methods: This study identified 44,932 Medicare beneficiaries with cancer who had received local therapy. Longitudinal opioid use was ascertained from Medicare Part D data. A risk score was calculated for each patient, and patients were categorized into low-, moderate-, and high-risk groups on the basis of the predicted probability of persistent opioid use. Model discrimination was assessed with receiver operating characteristic curves.Results: In the study cohort, 5.2% of the patients were chronic opioid users 1 to 2 years after the initiation of cancer treatment. The majority of the patients (64%) were at low risk and had a 1.2% probability of long-term opioid use. Moderate-risk patients (33% of the cohort) had a 5.6% probability of long-term opioid use. High-risk patients (3.5% of the cohort) had a 75% probability of long-term opioid use. The opioid risk score had an area under the receiver operating characteristic curve of 0.869.Conclusions: This study found that a cancer opioid risk score could accurately identify individuals with a high likelihood of long-term opioid use in a large, generalizable cohort of cancer survivors. Future research should focus on the implementation of these scores into clinical practice and how this could affect prescriber behavior and patient outcomes.Lay Summary: A novel 5-question clinical decision tool allows physicians treating patients with cancer to accurately predict which patients will persistently be using opioid medications after completing therapy. [ABSTRACT FROM AUTHOR]

Background: This study was designed to test the hypothesis that the effectiveness of intensive treatment for locoregionally advanced head and neck cancer (LAHNC) depends on the proportion of patients' overall event risk attributable to cancer.Methods: This study analyzed 22,339 patients with LAHNC treated in 81 randomized trials testing altered fractionation (AFX; Meta-Analysis of Radiotherapy in Squamous Cell Carcinomas of Head and Neck [MARCH] data set) or chemotherapy (Meta-Analysis of Chemotherapy in Head and Neck Cancer [MACH-NC] data set). Generalized competing event regression was applied to the control arms in MARCH, and patients were stratified by tertile according to the ω score, which quantified the relative hazard for cancer versus competing events. The classifier was externally validated on the MACH-NC data set. The study tested for interactions between the ω score and treatment effects on overall survival (OS).Results: Factors associated with a higher ω score were a younger age, a better performance status, an oral cavity site, higher T and N categories, and a p16-negative/unknown status. The effect of AFX on OS was greater in patients with high ω scores (hazard ratio [HR], 0.92; 95% confidence interval [CI], 0.85-0.99) and medium ω scores (HR, 0.91; 95% CI, 0.84-0.98) versus low ω scores (HR, 0.97; 95% CI, 0.90-1.05; P for interaction = .086). The effect of chemotherapy on OS was significantly greater in patients with high ω scores (HR, 0.81; 95% CI, 0.75-0.88) and medium ω scores (HR, 0.86; 95% CI, 0.78-0.93) versus low ω scores (HR, 0.96; 95% CI, 0.86-1.08; P for interaction = .011).Conclusions: LAHNC patients with a higher risk of cancer progression relative to competing mortality, as reflected by a higher ω score, selectively benefit from more intensive treatment. [ABSTRACT FROM AUTHOR]

Background: Hematologic toxicity is a critical problem limiting treatment delivery in cancer patients undergoing concurrent chemoradiotherapy. However, the extent to which anatomic variations in radiation dose limit chemotherapy delivery is poorly understood. A unique natural experiment arises in patients with head and neck and cervical cancer, who frequently undergo identical chemotherapy but receive radiation to different regions of the body. Comparing these cohorts can help elucidate to what extent hematologic toxicity is attributable to marrow radiation as opposed to chemotherapy. Methods: In this longitudinal cohort study, we compared hematologic toxicity and bone marrow compensatory response in 148 patients (90 cervix, 58 head/neck) undergoing chemoradiotherapy with concurrent weekly cisplatin 40 mg/m2. We used linear mixed effect models to compare baseline and time-varying peripheral cell counts and hemoglobin levels between cohorts. To assess bone marrow compensatory response, we measured the change in metabolically active bone marrow (ABM) volume on 18F-fluorodeoxyglucose positron emission tomography/computed tomography. Results: We observed greater reductions in log-transformed lymphocyte, platelet, and absolute neutrophil counts (ANC) for cervix compared to head/neck cancer patients (fixed effects for time-cohort interaction [95% CI]: lymphocytes, −0.06 [−0.09, −0.031]; platelets,−0.028 [-0.051, −0.0047]; ANC, −0.043 [−0.075, −0.011]). Mean ANC nadirs were also lower for cervical vs. head/neck cancer cohorts (2.20 vs. 2.85 × 103 per μL, p < 0.01). Both cohorts exhibited reductions in ABM volume within the radiation field, and increases in ABM volume in out-of-field areas, indicating varying compensatory response to radiation injury. Conclusions: Cervical cancer patients had faster decreases in ANC, lymphocyte, and platelet counts, and lower ANC nadirs, indicating a significant effect of pelvic irradiation on acute peripheral blood cell counts. Both cohorts exhibited a compensatory response with increased out-of-field bone marrow activity. [ABSTRACT FROM AUTHOR]

Background: Although opioids play a critical role in the management of cancer pain, the ongoing opioid epidemic has raised concerns regarding their persistent use and abuse. We lack data-driven tools in oncology to understand the risk of adverse opioid-related outcomes. This project seeks to identify clinical risk factors and create a risk score to help identify patients at risk of persistent opioid use and abuse.Methods: Within a cohort of 106 732 military veteran cancer survivors diagnosed between 2000 and 2015, we determined rates of persistent posttreatment opioid use, diagnoses of opioid abuse or dependence, and admissions for opioid toxicity. A multivariable logistic regression model was used to identify patient, cancer, and treatment risk factors associated with adverse opioid-related outcomes. Predictive risk models were developed and validated using a least absolute shrinkage and selection operator regression technique.Results: The rate of persistent opioid use in cancer survivors was 8.3% (95% CI = 8.1% to 8.4%); the rate of opioid abuse or dependence was 2.9% (95% CI = 2.8% to 3.0%); and the rate of opioid-related admissions was 2.1% (95% CI = 2.0% to 2.2%). On multivariable analysis, several patient, demographic, and cancer and treatment factors were associated with risk of persistent opioid use. Predictive models showed a high level of discrimination when identifying individuals at risk of adverse opioid-related outcomes including persistent opioid use (area under the curve [AUC] = 0.85), future diagnoses of opioid abuse or dependence (AUC = 0.87), and admission for opioid abuse or toxicity (AUC = 0.78).Conclusion: This study demonstrates the potential to predict adverse opioid-related outcomes among cancer survivors. With further validation, personalized risk-stratification approaches could guide management when prescribing opioids in cancer patients. [ABSTRACT FROM AUTHOR]

Background: African American (AA) men in the general US population are more than twice as likely to die of prostate cancer (PC) compared with non-Hispanic white (NHW) men. The authors hypothesized that receiving care through the Veterans Affairs (VA) health system, an equal-access medical system, would attenuate this disparity.Methods: A longitudinal, centralized database of >20 million veterans was used to assemble a cohort of 60,035 men (18,201 AA men [30.3%] and 41,834 NHW men [69.7%]) who were diagnosed with PC between 2000 and 2015.Results: AA men were more likely to live in regions with a lower median income ($40,871 for AA men vs $48,125 for NHW men; P < .001) and lower high school graduation rates (83% for AA men vs 88% for NHW men; P < .001). At the time of diagnosis, AA men were younger (median age, 63.0 years vs 66.0 years; P < .001) and had a higher prostate-specific antigen level (median, 6.7 ng/mL vs 6.2 ng/mL; P < .001), but were less likely to have Gleason score 8 to 10 disease (18.8% among AA men vs 19.7% among NHW men; P < .001), a clinical T classification ≥3 (2.2% vs 2.9%; P < .001), or distant metastatic disease (2.7% vs 3.1%; P = 0.01). The 10-year PC-specific mortality rate was slightly lower for AA men (4.4% vs 5.1%; P = .005), which was confirmed in multivariable competing-risk analysis (subdistribution hazard ratio, 0.85; 95% CI, 0.78-0.93; P < .001).Conclusions: AA men diagnosed with PC in the VA health system do not appear to present with more advanced disease or experience worse outcomes compared with NHW men, in contrast to national trends, suggesting that access to care is an important determinant of racial equity. [ABSTRACT FROM AUTHOR]

Background: Previous studies have reported conflicting information regarding the prognostic role of p16 in nonoropharyngeal head and neck squamous cell carcinoma (HNSCC).Methods: Using the US Veterans Affairs database, we analyzed 1448 patients with locoregionally advanced HNSCC and known p16 status diagnosed between 2005 and 2015 and treated with surgery, radiotherapy, or chemoradiotherapy. Tumor p16 status was determined through manual review of pathology reports of primary tumor specimens. Oropharyngeal (n = 1061) or nonoropharyngeal (n = 387; hypopharyngeal, laryngeal, or oral cavity) tumor site was determined from tumor registry data and manually reviewed for accuracy. We used multivariable Cox regression to analyze the effect of p16 status on overall survival (OS), cancer-specific survival (CSS), and competing mortality (CM) for oropharyngeal or nonoropharyngeal tumor sites. All statistical tests were two-sided.Results: In multivariable models adjusting for treatment, stage, age, comorbidity, and body mass index, patients with p16-positive tumors had improved OS, CSS, and CM compared with patients with p16-negative tumors in both oropharyngeal (OS: hazard ratio [HR] = 0.53, 95% confidence interval [CI] = 0.40 to 0.71, P < .001; CSS: HR = 0.50, 95% CI = 0.35 to 0.73, P < .001; CM: HR = 0.59, 95% CI = 0.38 to 0.93, P = .02) and nonoropharyngeal primary sites (OS: HR = 0.41, 95% CI = 0.25 to 0.69, P < .001; CSS: HR = 0.37, 95% CI = 0.18 to 0.77, P = .008; CM: HR = 0.46, 95% CI = 0.23 to 0.95, P = .04). The prognostic impact of p16 status did not statistically significantly differ by primary tumor site for OS, CSS, or CM (Pinteraction > .05).Conclusions: Our findings support the hypothesis that p16 has a similar prognostic role in both nonoropharyngeal and oropharyngeal cancer. Consideration should be given to increased testing for p16 in laryngeal, hypopharyngeal, and oral cavity primaries. [ABSTRACT FROM AUTHOR]

Purpose: Comorbidity is an independent predictor of mortality and treatment tolerance in head and neck cancer and should be considered with regard to treatment intensification. Multiple previously validated models can be used to evaluate comorbidity and propensity to benefit from intensive treatment, but they have not been directly compared. Materials and Methods: An online tool was developed and used to calculate the Charlson Comorbidity Index (CCI), Adult Comorbidity Evaluation-27 (ACE-27), Cumulative Illness Rating Scale for Geriatrics (CIRS-G), Geriatric 8 (G8), Cancer and Aging Research Group (CARG), and Generalized Competing Event (GCE) scores. To assess interrater variability, five evaluators independently calculated scores on a retrospective cohort of 20 patients. Correlation between models as well as age and performance status were calculated from a cohort of 40 patients. Results: The GCE and G8 models had an excellent (intraclass correlation coefficient and Fleiss' kappa ≥ 0.75) degree of interrater agreement. The CCI, ACE-27, CIRS-G, and CARG had a good (intraclass correlation coefficient and Fleiss' kappa 0.6-0.74) degree of interrater agreement. There was statistically significant correlation between models, especially with the CCI, ACE-27, and CIRS-G indices. Increased age was correlated with an increased CCI score and having moderate to severe comorbidity was correlated with the ACE-27 model. Except for the G8 model, the comorbidity indices were not associated with Eastern Cooperative Oncology Group performance status. Conclusion: We developed an online tool to calculate indices of comorbidity in patients with head and neck cancer with a high degree of reproducibility. Comorbidity is not strongly correlated with performance status and should be independently evaluated in patients. [ABSTRACT FROM AUTHOR]

Purpose Generalized competing event (GCE) models improve stratification of patients according to their risk of cancer events relative to competing causes of mortality. The potential impact of such methods on clinical trial power and cost, however, is uncertain. We sought to test the hypothesis that GCE models can reduce estimated clinical trial cost in elderly patients with cancer. Methods Patients with nonmetastatic head and neck (n = 9,677), breast (n = 22,929), or prostate cancer (n = 51,713) were sampled from the SEER-Medicare database. Using multivariable Cox proportional hazards models, we compared risk scores for all-cause mortality (ACM) and cancer-specific mortality (CSM) with GCE-based risk scores for each disease. We applied a cost function to estimate the cost and duration of clinical trials with a primary end point of overall survival in each population and in high-risk subpopulations. We conducted sensitivity analyses to examine model uncertainty. Results For the purpose of enriching subpopulations, GCE models reduced estimated clinical trial cost compared with Cox models of ACM and CSM in all disease sites. The relative cost reductions with GCE models compared with ACM and CSM models, respectively, were -68.4% and -14.4% in prostate cancer, -38.8% and -18.3% in breast cancer, and -17.1% and -4.1% in head and neck cancer. Cost savings in breast and prostate cancers were on the order of millions of dollars. The GCE model also reduced relative clinical trial duration compared with CSM and ACM models for all disease sites. The optimal risk score cutoff for clinical trial enrollment occurred near the top tertile for all disease sites. Conclusion GCE models have significant potential to improve clinical trial efficiency and reduce cost, with a potentially large impact in prostate and breast cancers. [ABSTRACT FROM AUTHOR]

Head and neck soft tissue sarcomas (HNSTSs) are rare and heterogeneous cancers in which radiation therapy (RT) has an important role in local tumor control (LC). The purpose of this study was to evaluate outcomes and patterns of treatment failure in patients with HNSTS treated with RT. A retrospective review was performed of adult patients with HNSTS treated with RT from January 1, 1998, to December 31, 2012. LC, locoregional control (LRC), disease-free survival (DFS), overall survival (OS), and predictors thereof were assessed. Forty-eight patients with HNSTS were evaluated. Five-year Kaplan-Meier estimates of LC, LRC, DFS, and OS were 87, 73, 63, and 83%, respectively. Angiosarcomas were found to be associated with worse LC, LRC, DFS, and OS. Patients over the age of 60 had lower rates of DFS. HNSTSs comprise a diverse group of tumors that can be managed with various treatment regimens involving RT. Angiosarcomas have higher recurrence and mortality rates. [ABSTRACT FROM AUTHOR]