Prognosticating in patients with advanced cancer—observational study comparing the accuracy of clinicians’ and patients’ estimates of survival

Gwilliam, Bridget; Keeley, Vaughan; Todd, Chris; Roberts, Chris; Gittins, Matthew; Kelly, Laura; Barclay, Stephen; Stone, Patrick

doi:10.1093/annonc/mds341

Cited by 64 publications

(58 citation statements)

References 26 publications

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“…Of the 42 studies included, 20 reported prognostic estimates using only a categorical approach [19, 20, 25–27, 30, 34, 36, 37, 40–42, 45–47, 49, 55, 56, 58, 60], 16 reported only continuous estimates [21, 22, 24, 28, 29, 31, 33, 38, 39, 44, 48, 50–53, 57] and 3 studies reported only probabilistic estimates [32, 43, 59]. Two studies used both categorical and continuous estimates [23, 54] and one study reported all three types of estimates [35].…”

Section: Resultsmentioning

confidence: 99%

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A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

et al. 2016

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BackgroundPrognostic accuracy in palliative care is valued by patients, carers, and healthcare professionals. Previous reviews suggest clinicians are inaccurate at survival estimates, but have only reported the accuracy of estimates on patients with a cancer diagnosis.ObjectivesTo examine the accuracy of clinicians’ estimates of survival and to determine if any clinical profession is better at doing so than another.Data SourcesMEDLINE, Embase, CINAHL, and the Cochrane Database of Systematic Reviews and Trials. All databases were searched from the start of the database up to June 2015. Reference lists of eligible articles were also checked.Eligibility CriteriaInclusion criteria: patients over 18, palliative population and setting, quantifiable estimate based on real patients, full publication written in English. Exclusion criteria: if the estimate was following an intervention, such as surgery, or the patient was artificially ventilated or in intensive care.Study Appraisal and Synthesis MethodsA quality assessment was completed with the QUIPS tool. Data on the reported accuracy of estimates and information about the clinicians were extracted. Studies were grouped by type of estimate: categorical (the clinician had a predetermined list of outcomes to choose from), continuous (open-ended estimate), or probabilistic (likelihood of surviving a particular time frame).Results4,642 records were identified; 42 studies fully met the review criteria. Wide variation was shown with categorical estimates (range 23% to 78%) and continuous estimates ranged between an underestimate of 86 days to an overestimate of 93 days. The four papers which used probabilistic estimates tended to show greater accuracy (c-statistics of 0.74–0.78). Information available about the clinicians providing the estimates was limited. Overall, there was no clear “expert” subgroup of clinicians identified.LimitationsHigh heterogeneity limited the analyses possible and prevented an overall accuracy being reported. Data were extracted using a standardised tool, by one reviewer, which could have introduced bias. Devising search terms for prognostic studies is challenging. Every attempt was made to devise search terms that were sufficiently sensitive to detect all prognostic studies; however, it remains possible that some studies were not identified.ConclusionStudies of prognostic accuracy in palliative care are heterogeneous, but the evidence suggests that clinicians’ predictions are frequently inaccurate. No sub-group of clinicians was consistently shown to be more accurate than any other.Implications of Key FindingsFurther research is needed to understand how clinical predictions are formulated and how their accuracy can be improved.

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Section: Resultsmentioning

confidence: 99%

“…The accuracy of the categorical prognostic estimates in the 21 studies for which percentage accuracy could be calculated are presented in Fig 2 [19, 20, 23, 25–27, 34–37, 40, 41, 45–47, 49, 54–56, 58, 60]. Two papers could not be included in the forest plot because the relevant data was not available.…”

Section: Resultsmentioning

confidence: 99%

A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

et al. 2016

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“…Prognostication is the essential element affecting treatment selection in patients with advanced lung cancer. However, practitioners are often inaccurate and can be overly optimistic when predicting survival in cancer patients, thus leading to excessive treatments [5][6][7][8] . Conversely, clinicians with limited experience in managing cancer patients might be prone to underestimating prognosis and might subsequently withhold life-prolonging treatments 5 .…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing Treatment Selection and Survival in Advanced Lung Cancer

et al. 2017

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Purpose Despite numerous breakthrough therapies, inoperable lung cancer still places a heavy burden on patients who might not be candidates for chemotherapy. To identify potential candidates for the newly emerging immunotherapy-based treatment paradigms, we explored the clinical and biologic factors affecting treatment decisions. MethodsWe retrospectively reviewed the records of patients diagnosed at our university-affiliated cancer centre between 1 January 2011 and 31 December 2013. Patient demographics, systemic treatment, and survival were examined.Results During the 3-year study period, 683 patients fitting the inclusion criteria were identified. First-line therapy was administered in 49.5% of patients; only 22.4% received further lines of therapy. The main reasons for withholding therapy were poor performance status [ps (43.2%)], rapidly deteriorating ps (31.9%), patient refusal of therapy (20.9%), and associated comorbidities (4%). Older age, the presence of brain metastasis at diagnosis, and non-small-cell histology were also associated with therapeutic restraint. Oncology referrals were infrequent in patients who did not receive therapy (32.2%). Older patients and those with a poor ps experienced superior survival when treatment was administered (hazard ratio: 0.25; 95% confidence interval: 0.16 to 0.38; and hazard ratio: 0.44; 95% confidence interval: 0.23 to 0.87 respectively; p < 0.001).Conclusions Advanced lung cancer still poses a therapeutic challenge, with a high proportion of patients being deemed unfit for therapy. This issue cannot be resolved until appropriate measures are taken to ensure the inclusion of older patients and those with a relatively poor ps in large clinical trials. Immunotherapy might be interesting in this setting, given that it appears to be more tolerable. Another consequential undertaking would be the deployment of strategies to reduce wait times during the diagnostic process for patients with a high index of suspicion for lung cancer.

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“…1e4 Previous surveys have revealed that the majority of patients want to know their prognoses, and their prognostic estimates were less accurate than those of health care professionals. 5,6 Almost all the patients wished for their doctor to be honest in communicating their prognoses, 7 but in reality, physicians' clinical predictions of survival (CPS) for patients with advanced cancer are often inaccurate, which considerably impacts end-of-life care. 8e11 Multiple previous studies revealed that physicians' estimates tend to be more optimistic than pessimistic.…”

Section: Introductionmentioning

confidence: 99%

The Accuracy of Physicians' Clinical Predictions of Survival in Patients With Advanced Cancer

Amano

Maeda

Shimoyama

et al. 2015

Journal of Pain and Symptom Management

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Prognosticating in patients with advanced cancer—observational study comparing the accuracy of clinicians’ and patients’ estimates of survival

Abstract: MDTs were better at predicting survival than doctors' or nurses' alone. Patients were substantially worse. Among nurses, recency of review was related to improved prognostic accuracy.

Cited by 64 publications

References 26 publications

A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

Factors Influencing Treatment Selection and Survival in Advanced Lung Cancer

The Accuracy of Physicians' Clinical Predictions of Survival in Patients With Advanced Cancer

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