Improved Method to Stratify Elderly Patients With Cancer at Risk for Competing Events.

PURPOSE: To compare a novel generalized competing event (GCE) model versus the standard Cox proportional hazards regression model for stratifying elderly patients with cancer who are at risk for competing events. METHODS: We identified 84,319 patients with nonmetastatic prostate, head and neck, and breast cancers from the SEER-Medicare database. Using demographic, tumor, and clinical characteristics, we trained risk scores on the basis of GCE versus Cox models for cancer-specific mortality and all-cause mortality. In test sets, we examined the predictive ability of the risk scores on the different causes of death, including second cancer mortality, noncancer mortality, and cause-specific mortality, using Fine-Gray regression and area under the curve. We compared how well models stratified subpopulations according to the ratio of the cumulative cause-specific hazard for cancer mortality to the cumulative hazard for overall mortality (ω) using the Akaike Information Criterion. RESULTS: In each sample, increasing GCE risk scores were associated with increased cancer-specific mortality and decreased competing mortality, whereas risk scores from Cox models were associated with both increased cancer-specific mortality and competing mortality. GCE models created greater separation in the area under the curve for cancer-specific mortality versus noncancer mortality (P < .001), indicating better discriminatory ability between these events. Comparing the GCE model to Cox models of cause-specific mortality or all-cause mortality, the respective Akaike Information Criterion scores were superior (lower) in each sample: prostate cancer, 28.6 versus 35.5 versus 39.4; head and neck cancer, 21.1 versus 29.4 versus 40.2; and breast cancer, 24.6 versus 32.3 versus 50.8. CONCLUSION: Compared with standard modeling approaches, GCE models improve stratification of elderly patients with cancer according to their risk of dying from cancer relative to overall mortality.

Fat composition changes in bone marrow during chemotherapy and radiation therapy.

PURPOSE: To quantify changes in bone marrow fat fraction and determine associations with peripheral blood cell counts. METHODS AND MATERIALS: In this prospective study, 19 patients received either highly myelotoxic treatment (radiation therapy plus cisplatin, 5-fluorouracil mitomycin C [FU/MMC], or cisplatin/5-FU/cetuximab) or less myelotoxic treatment (capecitabine-radiation therapy or no concurrent chemotherapy). Patients underwent MR imaging and venipuncture at baseline, midtreatment, and posttreatment visits. We performed mixed effects modeling of the mean proton density fat fraction (PDFF[%]) by linear time, treatment, and vertebral column region (lumbar [L]4-sacral [S]2 vs thoracic [T]10-L3 vs cervical[C]3-T9), while controlling for cumulative mean dose and other confounders. Spearman rank correlations were performed by white blood cell (WBC) counts versus the differences in PDFF(%) before and after treatment. RESULTS: Cumulative mean dose was associated with a 0.43% per Gy (P=.004) increase in PDFF(%). In the highly myelotoxic group, we observed significant changes in PDFF(%) per visit within L4-S2 (10.1%, P<.001) and within T10-L3 (3.93%, P=.01), relative to the reference C3-T9. In the less myelotoxic group, we did not observe significant changes in PDFF(%) per visit according to region. Within L4-S2, we observed a significant difference between treatment groups in the change in PDFF(%) per visit (5.36%, P=.04). Rank correlations of the inverse log differences in WBC versus the differences in PDFF(%) overall and within T10-S2 ranged from 0.69 to 0.78 (P<.05). Rank correlations of the inverse log differences in absolute neutrophil counts versus the differences in PDFF(%) overall and within L4-S2 ranged from 0.79 to 0.81 (P<.05). CONCLUSIONS: Magnetic resonance imaging fat quantification is sensitive to marrow composition changes that result from chemoradiation therapy. These changes are associated with peripheral blood cell counts. This study supports a rationale for bone marrow-sparing treatment planning to reduce the risk of hematologic toxicity.

Validated competing event model for the stage I-II endometrial cancer population.

PURPOSE/OBJECTIVES(S): Early-stage endometrial cancer patients are at higher risk of noncancer mortality than of cancer mortality. Competing event models incorporating comorbidity could help identify women most likely to benefit from treatment intensification. METHODS AND MATERIALS: 67,397 women with stage I-II endometrioid adenocarcinoma after total hysterectomy diagnosed from 1988 to 2009 were identified in Surveillance, Epidemiology, and End Results (SEER) and linked SEER-Medicare databases. Using demographic and clinical information, including comorbidity, we sought to develop and validate a risk score to predict the incidence of competing mortality. RESULTS: In the validation cohort, increasing competing mortality risk score was associated with increased risk of noncancer mortality (subdistribution hazard ratio [SDHR], 1.92; 95% confidence interval [CI], 1.60-2.30) and decreased risk of endometrial cancer mortality (SDHR, 0.61; 95% CI, 0.55-0.78). Controlling for other variables, Charlson Comorbidity Index (CCI) = 1 (SDHR, 1.62; 95% CI, 1.45-1.82) and CCI >1 (SDHR, 3.31; 95% CI, 2.74-4.01) were associated with increased risk of noncancer mortality. The 10-year cumulative incidences of competing mortality within low-, medium-, and high-risk strata were 27.3% (95% CI, 25.2%-29.4%), 34.6% (95% CI, 32.5%-36.7%), and 50.3% (95% CI, 48.2%-52.6%), respectively. With increasing competing mortality risk score, we observed a significant decline in omega (ω), indicating a diminishing likelihood of benefit from treatment intensification. CONCLUSION: Comorbidity and other factors influence the risk of competing mortality among patients with early-stage endometrial cancer. Competing event models could improve our ability to identify patients likely to benefit from treatment intensification.

Stereotactic body radiation therapy in octogenarians with stage I lung cancer.

BACKGROUND: The purpose of this study was to describe our clinical experience using stereotactic body radiation therapy (SBRT) to treat medically inoperable stage I non-small-cell lung cancer (NSCLC) in very elderly patients. PATIENTS AND METHODS: Twenty-four consecutive octogenarians with stage I NSCLC were treated with SBRT between 2007 and 2011 at a single center. Median prescription dose was 48 Gy (range, 48-56). Follow-up clinical examination and computed tomography (CT) were performed every 2 to 3 months. RESULTS: Median age was 85 years (range, 80-89). Twenty-three (96%) patients had peripheral tumors, and median tumor size was 22 mm (range, 11-49). Tissue diagnosis was obtained in 16 (67%) patients. Median follow-up for all patients was 27.6 months (range, 4.3-61.2). The 24-month disease-free survival was 77% (95% confidence interval [CI], 61%-97%). The 24-month overall survival (OS) was 74% (95% CI, 57%-94%). No local failure (LF) was observed during the period of observation. Nodal failure (NF) and distant failure (DF) occurred in 2 and 4 patients, respectively. The cumulative incidence of competing mortality at 24 months was estimated at 13% (95% CI, 3%-30%). No difference in outcomes with or without tissue diagnosis was observed. No grade ≥ 3 early or late treatment-related toxicities were observed. CONCLUSION: Octogenarians tolerate SBRT well, which makes it an attractive treatment option.

Cause-specific effects of radiotherapy and lymphadenectomy in stage I-II endometrial cancer: a population-based study.

BACKGROUND: Radiotherapy and lymphadenectomy have been associated with improved survival in population-based studies of endometrial cancer, which is in contrast with findings from randomized trials and meta-analyses. The primary study aim was to estimate the cause-specific effects of adjuvant radiotherapy and lymphadenectomy on competing causes of mortality. METHODS: We analyzed Surveillance, Epidemiology, and End Results (SEER) data from 1988 to 2006. The sample comprised 58172 patients with stage I and II endometrial adenocarcinoma. Patients were risk stratified by stage, grade, and age. Cumulative incidences and cause-specific hazards of competing causes of mortality were estimated according to treatment. All statistical tests were two-sided. RESULTS: Pelvic radiotherapy was associated with statistically significantly increased endometrial cancer mortality (hazard ratio [HR] = 1.66; 95% confidence interval [CI] = 1.52 to 1.82) in all stage I and II patients and decreased noncancer mortality in intermediate and high-risk stage I and II patients (HR = 0.82; 95% CI = 0.77 to 0.89). Lymphadenectomy was associated with increased endometrial cancer mortality in stage I patients (HR = 1.27; 95% CI = 1.16 to 1.39), decreased endometrial cancer mortality in stage II patients (HR = 0.61; 95% CI = 0.52 to 0.72), and decreased noncancer mortality in both stage I and II patients (HR = 0.84; 95% CI = 0.80 to 0.88). Effects of radiotherapy and lymphadenectomy on second cancer mortality varied according to risk strata. CONCLUSIONS: Radiotherapy and lymphadenectomy are associated with statistically significantly reduced noncancer mortality in stage I and II endometrial cancer. The improved overall survival associated with these treatments reported from SEER studies is largely attributable to their selective application in healthier patients rather than their effects on endometrial cancer.

Competing event risk stratification may improve the design and efficiency of clinical trials: secondary analysis of SWOG 8794.

BACKGROUND: Composite endpoints can be problematic in the presence of competing risks when a treatment does not affect events comprising the endpoint equally. METHODS: We conducted secondary analysis of SWOG 8794 trial of adjuvant radiation therapy (RT) for high-risk post-operative prostate cancer. The primary outcome was metastasis-free survival (MFS), defined as time to first occurrence of metastasis or death from any cause (competing mortality (CM)). We developed separate risk scores for time to metastasis and CM using competing risks regression. We estimated treatment effects using Cox models adjusted for risk scores and identified an enriched subgroup of 75 patients at high risk of metastasis and low risk of CM. RESULTS: The mean CM risk score was significantly lower in the RT arm vs. control arm (p=0.001). The effect of RT on MFS (HR 0.70; 95% CI, 0.53-0.92; p=0.010) was attenuated when controlling for metastasis and CM risk (HR 0.76; 95% CI, 0.58-1.00; p=0.049), and the effect of RT on overall survival (HR 0.73; 95% CI, 0.55-0.96; p=0.02) was no longer significant when controlling for metastasis and CM risk (HR 0.80; 95% CI, 0.60-1.06; p=0.12). Compared to the whole sample, the enriched subgroup had the same 10-year incidence of MFS (40%; 95% CI, 22-57%), but a higher incidence of metastasis (30% (95% CI, 15-47%) vs. 20% (95% CI, 15-26%)). A randomized trial in the subgroup would have achieved 80% power with 56% less patients (313 vs. 709, respectively). CONCLUSION: Stratification on competing event risk may improve the efficiency of clinical trials.