Intensity-Modulated Radiation Therapy, Proton Therapy, or Conformal Radiation Therapy and Morbidity and Disease Control in Localized Prostate Cancer

Sheets, Nathan; Goldin, Gregg H.; Meyer, Anne‐Marie; Wu, Yang; Chang, Yeon S.; Stürmer, Til; Holmes, Jordan A.; Reeve, Bryce B.; Godley, Paul A.; Carpenter, William R.; Chen, Ronald C.

doi:10.1001/jama.2012.460

Cited by 392 publications

(144 citation statements)

References 43 publications

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“…3.0GI 13% vs 5% P ≤ 0.001GU 20% vs 12% P = 0.01IMRT reduces GI but increases GU toxicityAcute related to late toxicityVora [18](Mayo)2007( n = 416)3D-CRT vs IMRT n = 271 vs 1455 years3D-CRT vs IMRT68.4 (66–71) Gy vs 75.6 (70.2–77.4) Gy74.4% vs 84.6% P = 0.032 6CTCAE ver. 4.0GI 16% vs 24%GU 29% vs 22%high dose IMRT improved PSA control in intermediate and high risk groupsSharma [19](Fox Chase)2011( n = 293)3D-CRT + ADT vs IMRT + ADT n = 170 vs 12386 months vs40 monthsNAFox chase modified LENTGI 20% vs 8% P = 0.01GU 6.5% vs 4.8%IMRT reduced GI toxicityBekekman [20] (UPEN)2011( n = 12 598)3D-CRT vs IMRT n = 6753 vs 584524 monthsSEER–Medicare databaseNA aged 65 years or olderNAMedicare patient claim composite bowel complicationbowel 22.5% vs 18.8%; HR 0.86proctitis/hemorrhage; HR 0.78IMRT slightly reduced GI toxicitySheets [21](North Carolina)2012( n = 12 976)3D-CRT vs IMRT (vs proton) n = 6753 vs 5845 vs 136844 months vs 64 months and 46 months vs 50 monthsSEER–Medicare databaseNA (propensity score–adjusted analyses)NAMedicare patient claimGI 14.7 vs 13.4 per 100 person-yearsHip fracture 1.0 vs 0.8, ED 5.3 vs 5.9IMRT less GI toxicity and hip fractures, more ED than 3D-CRT(IMRT less GI toxicity than proton 12.2 vs 17.8)Michalsky [22] (RTOG 0126)2013( n = 748)RCT: 3D-CRT vs IMRT n = 491 vs 2574.6 years vs 3.5 years79.2 GyNACTC ver. 2.0 RTOG/EORTCGI 22% vs 15.1% P = 0.039GU NAIMRT reduced GI toxicity but not significant in multivariate analysis IMRT Alicikus [23] (MSK)2011( n = 170)Long-term follow-up...…”

Section: Literature Reviewmentioning

confidence: 99%

Transitioning from conventional radiotherapy to intensity-modulated radiotherapy for localized prostate cancer: changing focus from rectal bleeding to detailed quality of life analysis

Yamazaki

Nakamura

Nishimura

et al. 2014

Journal of Radiation Research

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With the advent of modern radiation techniques, we have been able to deliver a higher prescribed radiotherapy dose for localized prostate cancer without severe adverse reactions. We reviewed and analyzed the change of toxicity profiles of external beam radiation therapy (EBRT) from the literature. Late rectal bleeding is the main adverse effect, and an incidence of >20% of Grade ≥2 adverse events was reported for 2D conventional radiotherapy of up to 70 Gy. 3D conformal radiation therapy (3D-CRT) was found to reduce the incidence to ∼10%. Furthermore, intensity-modulated radiation therapy (IMRT) reduced it further to a few percentage points. However, simultaneously, urological toxicities were enhanced by dose escalation using highly precise external radiotherapy. We should pay more attention to detailed quality of life (QOL) analysis, not only with respect to rectal bleeding but also other specific symptoms (such as urinary incontinence and impotence), for two reasons: (i) because of the increasing number of patients aged >80 years, and (ii) because of improved survival with elevated doses of radiotherapy and/or hormonal therapy; age is an important prognostic factor not only for prostate-specific antigen (PSA) control but also for adverse reactions. Those factors shift the main focus of treatment purpose from survival and avoidance of PSA failure to maintaining good QOL, particularly in older patients. In conclusion, the focus of toxicity analysis after radiotherapy for prostate cancer patients is changing from rectal bleeding to total elaborate quality of life assessment.

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Section: Literature Reviewmentioning

confidence: 99%

Transitioning from conventional radiotherapy to intensity-modulated radiotherapy for localized prostate cancer: changing focus from rectal bleeding to detailed quality of life analysis

Yamazaki

Nakamura

Nishimura

et al. 2014

Journal of Radiation Research

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“…Examples include, but are not limited to, cancer treatments (Sheets et al, 2012; Zeliadt et al, 2014). However, whether calendar time is an instrument is not always known, and incorrectly characterizing a variable as an instrument (and thus not controlling for the variable) when in fact it is a confounder leads to unmeasured confounding.…”

Section: Discussion Limitations and Conclusionmentioning

confidence: 99%

Model Misspecification When Excluding Instrumental Variables from PS Models in Settings Where Instruments Modify the Effects of Covariates on Treatment

Wyss

Ellis

Brookhart

et al. 2014

Epidemiologic Methods

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Theory and simulations show that variables affecting the outcome only through exposure, known as instrumental variables (IVs), should be excluded from propensity score (PS) models. In pharmacoepidemiologic studies based on automated healthcare databases, researchers will sometimes use a single PS model to control for confounding when evaluating the effect of a treatment on multiple outcomes. Because these “full” models are not constructed with a specific outcome in mind, they will usually contain a large number of IVs for any individual study or outcome. If researchers subsequently decide to evaluate a subset of the outcomes in more detail, they can construct reduced “outcome-specific” models that exclude IVs for the particular study. Accurate estimates of PSs that do not condition on IVs, however, can be compromised when simply excluding instruments from the full PS model. This misspecification may have a negligible impact on effect estimates in many settings, but is likely to be more pronounced for situations where instruments modify the effects of covariates on treatment (instrument-confounder interactions). In studies evaluating drugs during early dissemination, the effects of covariates on treatment are likely modified over calendar time and IV-confounder interaction effects on treatment are likely to exist. In these settings, refitting more flexible PS models after excluding IVs and IV-confounder interactions can work well. The authors propose an alternative method based on the concept of marginalization that can be used to remove the negative effects of controlling for IVs and IV-confounder interactions without having to refit the full PS model. This method fits the full PS model, including IVs and IV-confounder interactions, but marginalizes over values of the instruments. Fitting more flexible PS models after excluding IVs or using the full model to marginalize over IVs can prevent model misspecification along with the negative effects of balancing instruments in certain settings.

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“…These might include differences in health seeking behaviors (screening or diagnostic workups for suspected health problems) [33], more frequent lab testing for potential liver or kidney damage if the medication is suspected to increase risk [34], or use of follow-up colonoscopies after selected types of radiation [35, 36]. This would decrease the proportion of individuals who have the outcome who are incorrectly classified as unaffected among patients with the exposure.…”

Section: Clinical Outcomesmentioning

confidence: 99%

Misclassification in Administrative Claims Data: Quantifying the Impact on Treatment Effect Estimates

2014

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Misclassification is present in nearly every epidemiologic study, yet is rarely quantified in analysis in favor of a focus on random error. In this review, we discuss past and present wisdom on misclassification and what measures should be taken to quantify this influential bias, with a focus on bias in pharmacoepidemiologic studies. To date, pharmacoepidemiology primarily utilizes data obtained from administrative claims, a rich source of prescription data but susceptible to bias from unobservable factors including medication sample use, medications filled but not taken, health conditions that are not reported in the administrative billing data, and inadequate capture of confounders. Due to the increasing focus on comparative effectiveness research, we provide a discussion of misclassification in the context of an active comparator, including a demonstration of treatment effects biased away from the null in the presence of nondifferential misclassification. Finally, we highlight recently developed methods to quantify bias and offer these methods as potential options for strengthening the validity and quantifying uncertainty of results obtained from pharmacoepidemiologic research.

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Intensity-Modulated Radiation Therapy, Proton Therapy, or Conformal Radiation Therapy and Morbidity and Disease Control in Localized Prostate Cancer

Cited by 392 publications

References 43 publications

Transitioning from conventional radiotherapy to intensity-modulated radiotherapy for localized prostate cancer: changing focus from rectal bleeding to detailed quality of life analysis

Transitioning from conventional radiotherapy to intensity-modulated radiotherapy for localized prostate cancer: changing focus from rectal bleeding to detailed quality of life analysis

Model Misspecification When Excluding Instrumental Variables from PS Models in Settings Where Instruments Modify the Effects of Covariates on Treatment

Misclassification in Administrative Claims Data: Quantifying the Impact on Treatment Effect Estimates

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