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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., (© 2020 American Cancer Society.)

Background: To evaluate the effects of administering chemotherapy following surgery, or following surgery plus radiotherapy (known as adjuvant chemotherapy) in patients with early stage non-small cell lung cancer (NSCLC),we performed two systematic reviews and meta-analyses of all randomised controlled trials using individual participant data. Results were first published in The Lancet in 2010., Objectives: To compare, in terms of overall survival, time to locoregional recurrence, time to distant recurrence and recurrence-free survival:A. Surgery versus surgery plus adjuvant chemotherapyB. Surgery plus radiotherapy versus surgery plus radiotherapy plus adjuvant chemotherapyin patients with histologically diagnosed early stage NSCLC.(2)To investigate whether or not predefined patient subgroups benefit more or less from cisplatin-based chemotherapy in terms of survival., Search Methods: We supplemented MEDLINE and CANCERLIT searches (1995 to December 2013) with information from trial registers, handsearching relevant meeting proceedings and by discussion with trialists and organisations., Selection Criteria: We included trials of a) surgery versus surgery plus adjuvant chemotherapy; and b) surgery plus radiotherapy versus surgery plus radiotherapy plus adjuvant chemotherapy, provided that they randomised NSCLC patients using a method which precluded prior knowledge of treatment assignment., Data Collection and Analysis: We carried out a quantitative meta-analysis using updated information from individual participants from all randomised trials. Data from all patients were sought from those responsible for the trial. We obtained updated individual participant data (IPD) on survival, and date of last follow-up, as well as details of treatment allocated, date of randomisation, age, sex, histological cell type, stage, and performance status. To avoid potential bias, we requested information for all randomised patients, including those excluded from the investigators' original analyses. We conducted all analyses on intention-to-treat on the endpoint of survival. For trials using cisplatin-based regimens, we carried out subgroup analyses by age, sex, histological cell type, tumour stage, and performance status., Main Results: We identified 35 trials evaluating surgery plus adjuvant chemotherapy versus surgery alone. IPD were available for 26 of these trials and our analyses are based on 8447 participants (3323 deaths) in 34 trial comparisons. There was clear evidence of a benefit of adding chemotherapy after surgery (hazard ratio (HR)= 0.86, 95% confidence interval (CI)= 0.81 to 0.92, p< 0.0001), with an absolute increase in survival of 4% at five years.We identified 15 trials evaluating surgery plus radiotherapy plus chemotherapy versus surgery plus radiotherapy alone. IPD were available for 12 of these trials and our analyses are based on 2660 participants (1909 deaths) in 13 trial comparisons. There was also evidence of a benefit of adding chemotherapy to surgery plus radiotherapy (HR= 0.88, 95% CI= 0.81 to 0.97, p= 0.009). This represents an absolute improvement in survival of 4% at five years.For both meta-analyses, we found similar benefits for recurrence outcomes and there was little variation in effect according to the type of chemotherapy, other trial characteristics or patient subgroup.We did not undertake analysis of the effects of adjuvant chemotherapy on quality of life and adverse events. Quality of life information was not routinely collected during the trials, but where toxicity was assessed and mentioned in the publications, it was thought to be manageable. We considered the risk of bias in the included trials to be low., Authors' Conclusions: Results from 47 trial comparisons and 11,107 patients demonstrate the clear benefit of adjuvant chemotherapy for these patients, irrespective of whether chemotherapy was given in addition to surgery or surgery plus radiotherapy. This is the most up-to-date and complete systematic review and individual participant data (IPD) meta-analysis that has been carried out.

Several R(2) -type measures have been proposed to evaluate the predictive ability of a survival model. In Part I, we classified the measures into four categories and studied the measures in the explained variation category. In this paper, we study the remaining measures in a similar fashion, discussing their strengths and shortcomings. Simulation studies are used to examine the performance of the measures with respect to the criteria we set out in Part I. Our simulation studies showed that among the measures studied in this paper, the measures proposed by Kent and O'Quigley ρ(W)(2) (and its approximation ρ(W,A)(2)) and Schemper and Kaider R(SK)(2) perform better with respect to our criteria. However, our investigations showed that ρ(W)(2) is adversely affected by the distribution of covariate and the presence of influential observations. The results show that the other measures perform poorly, primarily because they are affected either by the degree of censoring or the follow-up period., (Copyright © 2012 John Wiley & Sons, Ltd.)

Measures of predictive ability play an important role in quantifying the clinical significance of prognostic factors. Several measures have been proposed to evaluate the predictive ability of survival models in the last two decades, but no single measure is consistently used. The proposed measures can be classified into the following categories: explained variation, explained randomness, and predictive accuracy. The three categories are conceptually different and are based on different principles. Several new measures have been proposed since Schemper and Stare's study in 1996 on some of the existing measures. This paper is the first of two papers that study the proposed measures systematically by applying a set of criteria that a measure of predictive ability should possess in the context of survival analysis. The present paper focuses on the explained variation category, and part II studies the proposed measures in the other categories. Simulation studies are used to examine the performance of five explained variation measures with respect to these criteria, discussing their strengths and shortcomings. Our simulation studies show that the measures proposed by Kent and O'Quigley, R(PM)(2), and Royston and Sauerbrei, R(D)(2), appear to be the best overall at quantifying predictive ability. However, it should be noted that neither measure is perfect; R(PM)(2) is sensitive to outliers and R(D)(2) to (marked) non-normality of the distribution of the prognostic index. The results show that the other measures perform poorly, primarily because they are adversely affected by censoring., (Copyright © 2011 John Wiley & Sons, Ltd.)