Menon, Mani

142 Background: Despite documented oncological benefit, postoperative adjuvant radiotherapy (aRT) utilization in prostate cancer (PCa) patients is still limited in the US. We aimed to develop and internally validate a risk stratification tool incorporating the Decipher score, along with routinely available clinicopathologic features, to identify patients who would benefit the most from aRT. Methods: Our cohort included a total of 512 PCa patients treated with RP at one of four US academic centers between 1990-2010. All patients had ≥ pT3a disease, positive margins, and/or pathologic lymph node invasion (LNI). Multivariable Cox regression analysis (MVA) tested the relationship between available predictors (including Decipher score) and clinical recurrence (CR), which were then used to develop a novel risk stratification tool. Our study adhered to the TRIPOD guidelines for development of prognostic models. Results: Overall, 21.9% patients received aRT. Median follow-up in censored patients was 8.3 years. The 10-year CR rate was 4.9% vs. 17.4% in patients treated with aRT vs. initial observation (p < 0.001). Pathological T3b/T4 stage, Gleason score 8-10, LNI and Decipher score > 0.6 were independent predictors of CR (all p < 0.01) Cumulative number of risk factors was 0, 1, 2, and 3-4 in respectively 46.5, 28.9, 17.2, and 7.4% of patients. Adjuvant RT was associated with decreased CR rate in patients with ≥ 2 risk factors (10-year CR rate 10.1% in aRT vs. 42.1% in initial observation, p = 0.008), but not in those with < 2 risk factors (p = 0.23). Conclusions: Utilizing the novel model to indicate aRT might reduce overtreatment, decrease unnecessary side effects, and reduce risk of CR in the subset of patients (~25% of all patients with aggressive pathological disease) who really benefit from this therapy.

Purpose Despite documented oncologic benefit, use of postoperative adjuvant radiotherapy (aRT) in patients with prostate cancer is still limited in the United States. We aimed to develop and internally validate a risk-stratification tool incorporating the Decipher score, along with routinely available clinicopathologic features, to identify patients who would benefit the most from aRT. Patient and Methods Our cohort included 512 patients with prostate cancer treated with radical prostatectomy at one of four US academic centers between 1990 and 2010. All patients had ≥ pT3a disease, positive surgical margins, and/or pathologic lymph node invasion. Multivariable Cox regression analysis tested the relationship between available predictors (including Decipher score) and clinical recurrence (CR), which were then used to develop a novel risk-stratification tool. Our study adhered to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for development of prognostic models. Results Overall, 21.9% of patients received aRT. Median follow-up in censored patients was 8.3 years. The 10-year CR rate was 4.9% vs. 17.4% in patients treated with aRT versus initial observation ( P < .001). Pathologic T3b/T4 stage, Gleason score 8-10, lymph node invasion, and Decipher score > 0.6 were independent predictors of CR (all P < .01). The cumulative number of risk factors was 0, 1, 2, and 3 to 4 in 46.5%, 28.9%, 17.2%, and 7.4% of patients, respectively. aRT was associated with decreased CR rate in patients with two or more risk factors (10-year CR rate 10.1% in aRT v 42.1% in initial observation; P = .012), but not in those with fewer than two risk factors ( P = .18). Conclusion Using the new model to indicate aRT might reduce overtreatment, decrease unnecessary adverse effects, and reduce risk of CR in the subset of patients (approximately 25% of all patients with aggressive pathologic disease in our cohort) who benefit from this therapy.

Purpose The role of adjuvant radiotherapy (aRT) in treating patients with pN1 prostate cancer is controversial. We tested the hypothesis that the impact of aRT on cancer-specific mortality (CSM) in these individuals is related to tumor characteristics. Methods We evaluated 1,107 patients with pN1 prostate cancer treated with radical prostatectomy and anatomically extended pelvic lymph node dissection between 1988 and 2010 at two tertiary care centers. All patients received adjuvant hormonal therapy with or without aRT. Regression tree analysis stratified patients into risk groups on the basis of their tumor characteristics and the corresponding CSM rate. Cox regression analysis tested the relationship between aRT and CSM rate, as well as overall mortality (OM) rate in each risk group separately. Results Overall, 35% of patients received aRT. At multivariable analysis, aRT was associated with more favorable CSM rate (hazard ratio [HR], 0.37; P < .001). However, when patients were stratified into risk groups, only two groups of men benefited from aRT: (1) patients with positive lymph node (PLN) count ≤ 2, Gleason score 7 to 10, pT3b/pT4 stage, or positive surgical margins (HR, 0.30; P = .002); and (2) patients with PLN count of 3 to 4 (HR, 0.21; P = .02), regardless of other tumor characteristics. These results were confirmed when OM was examined as an end point. Conclusion The beneficial impact of aRT on survival in patients with pN1 prostate cancer is highly influenced by tumor characteristics. Men with low-volume nodal disease (≤ two PLNs) in the presence of intermediate- to high-grade, non–specimen-confined disease and those with intermediate-volume nodal disease (three to four PLNs) represent the ideal candidates for aRT after surgery.

BACKGROUNDApproximately 1.7 million individuals per year are affected with health care‐associated infections (HAIs) in the United States. The authors examined trends in the incidence of HAI after major cancer surgery (MCS) and risk factors for HAI to describe the effects of HAI on mortality after MCS.METHODSPatients undergoing 1 of 8 MCS procedures within the Nationwide Inpatient Sample between 1999 and 2009 were identified (n = 2,502,686). Generalized linear regression models were used to estimate the impact of the primary predictors (procedure type, age, sex, race, insurance status, Charlson comorbidity index, hospital volume, and hospital bed size) on the odds of HAI and in‐hospital mortality. Trends in incidence were evaluated with linear regression.RESULTSOverall, MCS‐associated HAI incidence increased 2.7% per year (P < .001), whereas mortality decreased 1.3% per year (P < .001). Male gender (odds ratio [OR], 1.12, 95% confidence interval [CI], 1.10‐1.14), advancing age (OR, 1.02; 95% CI, 1.02‐1.02), black race (OR, 1.26; 95% CI, 1.21‐1.31), ≥1 comorbidities (OR, from 1.08 [95% CI, 1.04‐1.13] to 1.31 [95% CI, 1.27‐1.35]), and nonprivate insurance (OR, from 1.18 [95% CI, 1.15‐1.22] to 1.67 [95% CI, 1.59‐1.76]) were associated with an increased odds of HAI on multivariable analysis. Conversely, increasing hospital volume was associated with lower odds of HAI (OR, 0.999; 95% CI, 0.99‐0.99). Patients with MCS‐associated HAI had increased odds of mortality (OR, 8.66; 95% CI, 8.51‐8.82).CONCLUSIONSBetween 1999 and 2009, the incidence of MCS‐associated HAI events increased; however, HAI‐associated mortality decreased. That said, significant disparities exist in the hospital and demographic attributes associated with MCS‐associated HAI, with attendant health policy implications. Moreover, HAI remains detrimentally linked to mortality during hospitalization. Cancer 2013;119:2317–2324. © 2013 American Cancer Society.