Development of Indicators to Assess Quality of Care for Prostate Cancer

Nag, Nupur; Millar, Jeremy; Davis, Ian D.; Costello, Shaun; Duthie, James B; Mark, Stephen; Delprado, Warick; Smith, David P.; Pryor, David; Galvin, David; Sullivan, Frank; Murphy, Áine C.; Roder, David; Elsaleh, Hany; Currow, David C.; White, Craig; Skala, Marketa; Moretti, Kim; Walker, Tony; Ieso, Paolo De; Brooks, Andrew J.; Heathcote, Peter; Frydenberg, Mark; Thavaseelan, Jeffery; Evans, Sue

doi:10.1016/j.euf.2016.01.016

Cited by 27 publications

(25 citation statements)

References 24 publications

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“…The presence of positive surgical margins (PSMs) after radical prostatectomy (RP) is associated with the risk of biochemical relapse and is considered a measure of surgical quality . However, results from studies evaluating the possible unfavorable long‐term effects of PSMs on prostate cancer‐specific mortality have been inconsistent, and the question of whether PSMs after prostate cancer surgery should be of concern has been discussed …”

Section: Introductionmentioning

confidence: 99%

“…and is considered a measure of surgical quality. 1 However, results from studies evaluating the possible unfavorable long-term effects of PSMs on prostate cancer-specific mortality have been inconsistent, 2,3 and the question of whether PSMs after prostate cancer surgery should be of concern has been discussed. 4 Only a few large studies have examined the impact of PSMs on endpoints other than biochemical relapse, including local progression, castrate-resistant prostate cancer, and the development of the metastatic disease.…”

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confidence: 99%

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Impact of positive surgical margins on secondary treatment, palliative radiotherapy and prostate cancer‐specific mortality. A population‐based study of 13 198 patients

et al. 2019

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Background The results of studies evaluating the impact of positive surgical margins on prostate cancer‐specific mortality have been inconsistent. We, therefore, evaluated the impact of surgical margin status on subsequent secondary treatment, palliative radiotherapy, and prostate cancer‐specific mortality. Methods A total of 14 837 men treated with radical prostatectomy (RP) during the period 2001 to 2015 were identified from the Cancer Registry of Norway. Of those, 13 198 (89%) patients had complete data on the preoperative prostate‐specific antigen level, pathological T‐category, Gleason score in the prostatectomy specimen, and margin status. Multivariable Cox proportional hazards models were used to evaluate the risk, and flexible parametric models for the cumulative incidence were fitted to predict the probabilities of secondary treatment (salvage radiotherapy or prophylactic breast radiation), palliative radiotherapy, and prostate cancer‐specific mortality. Results After a median follow‐up time of 5.2 years (3591 patients with ≥8 years of follow‐up), positive surgical margins (PSMs) were independently predictive of secondary treatment (hazard ratio [HR] = 2.43, 95% confidence interval [CI] = 2.21‐2.66) and palliative radiotherapy (HR = 1.45, 95% CI = 1.03‐2.05). After 10 years, the absolute increased risk for palliative radiotherapy in patients with PSMs after RP varied between 0.1% in pT2 tumors with a Gleason score of 6, to 12% for pT3b tumors with a Gleason score of 9 to 10. PSMs were not independently associated with prostate cancer‐specific mortality (HR = 1.14, 95% CI = 0.82‐1.59). Conclusion PSMs were associated with increased application of secondary treatment and palliative radiotherapy but were not predictive of prostate cancer‐specific mortality. As the use of palliative radiotherapy was only marginally increased in patients with PSMs and the lowest‐risk disease characteristics, avoiding PSMs may be of greatest prognostic relevance in patients with higher‐risk disease characteristics.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Impact of positive surgical margins on secondary treatment, palliative radiotherapy and prostate cancer‐specific mortality. A population‐based study of 13 198 patients

et al. 2019

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“…(4) PCOR-Vic collects data on aspects relating to the diagnosis, treatment, quality of life and outcomes of men diagnosed with CaP. (5) Quality of care is examined using specific quality of care indicators (see supplementary Table 1);; selected after a literature review and a prioritisation process (modified Delphi process (6)) which considered the importance and feasibility of each proposed quality indicator. Indicators were categorised according to whether they assessed structures, processes or outcomes of care.…”

Section: Introductionmentioning

confidence: 99%

(Dis)concordance of comorbidity data across ICD codes, medical charts, and self-reports

Sheriffdeen

Millar

Martin

et al. 2019

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Background Benchmarking outcomes across settings commonly requires risk-adjustment for co-morbidities that must be derived from extant sources that were designed for other purposes. A question arises as to the extent to which differing available sources for health data will be concordant when inferring the type and severity of co-morbidities, how close these are to the “truth”. We studied the level of concordance for same-patient comorbidity data extracted from administrative data (coded from International Classification of Diseases, Australian modification,10th edition [ICD-10AM]), from the medical chart audit, and data self-reported by men with prostate cancer who had undergone a radical prostatectomy.Methods We included six hospitals (5 public and 1 private) contributing to the Prostate Cancer Outcomes Registry-Victoria (PCOR-Vic) in the study. We listed eligible patients from the PCOR-Vic who underwent a radical prostatectomy between January 2017 and April 2018 for the Health Information Manager in each hospital, who provided each patient’s associated ICD-10AM comorbidity codes. Medical charts were reviewed to extract comorbidities used to generate the Charlson Comorbidity Index. The self-reported comorbidity questionnaire (SCQ) was distributed through PCOR-Vic to eligible men.Results The percentage agreement between the administrative data, medical charts and self-reports ranged from 92% to 99% in the 122 patients (from 217 eligible participants, 56%), who responded to the questionnaire. The prevalence-adjusted bias-adjusted kappa (PABAK) coefficient was from 0.83 to 0.98 for all conditions aside from cancer, reflecting a strong level of agreement for the absence of comorbidities. Conversely, the presence of comorbidities showed a poor level of agreement between data sources. There was concordance on 213/277 (77%) comorbidities when comparing medical charts and administrative data; 102/238 (30%) comorbidities when comparing medical chart and self-reports; and 34/150 (23%) comorbidities when comparing administrative data and self-reports.Conclusion Relying on a single data source to generate comorbidity indices for risk-modelling purposes may fail to capture the reality of a patient’s disease profile. There does not appear to be a ‘gold-standard’ data source for the collection of data on comorbidities.

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“…Most indicators (28/55 (51%)) were treatment- Previous cohort studies have demonstrated unnecessary and costly routine bone scans and 229 computed tomography scans being performed for men with asymptomatic low-risk disease 14, 230 15 . Conversely, there remains suboptimal use in high-risk men 16 despite recommendations 13,17 .…”

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confidence: 99%

“…A treatment indicator which received the greatest support was curative treatment being 243 instigated in high-risk patients within 12 months. Although multimodality therapy is often 244 recommended for high-risk PCa 13,22,23 , the National Prostate Cancer Audit in UK reported 245 that 39% of men with high-risk disease were undertreated with ADT monotherapy 24 .…”

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Quality Indicators for Global Benchmarking of Localized Prostate Cancer Management

et al. 2018

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We developed a set of quality indicators to measure prostate cancer care using numerous international evidence-based clinical guidelines. These indicators will be pilot tested in the TrueNTH Global Registry. Reports comparing indicator performance will subsequently be distributed to groups at participating sites with the purpose of improving the consistency and quality of prostate cancer management on a global basis.

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Development of Indicators to Assess Quality of Care for Prostate Cancer

Cited by 27 publications

References 24 publications

Impact of positive surgical margins on secondary treatment, palliative radiotherapy and prostate cancer‐specific mortality. A population‐based study of 13 198 patients

Impact of positive surgical margins on secondary treatment, palliative radiotherapy and prostate cancer‐specific mortality. A population‐based study of 13 198 patients

(Dis)concordance of comorbidity data across ICD codes, medical charts, and self-reports

Quality Indicators for Global Benchmarking of Localized Prostate Cancer Management

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