Study of prognostic markers in advanced cancer
dc.contributor.advisor
Laird, Barry
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dc.contributor.advisor
Fallon, Marie
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dc.contributor.author
Simmons, Claribel Patrice Louise
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dc.contributor.sponsor
Medical Research Council (MRC)
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dc.date.accessioned
2019-07-24T14:48:08Z
dc.date.available
2019-07-24T14:48:08Z
dc.date.issued
2019-07-06
dc.description.abstract
BACKGROUND:
Prognostication is a core skill fundamental to the clinical management of
patients with advanced cancer. This skill is exercised to guide appropriate clinical
decisions, plan supportive services and allocate resource utilisation.
Prognostication
by clinicians is often erroneous, optimistic, informal and subjective. Clinicians base
survival predictions upon clinical experience, clinical intuition and knowledge of cancer
trajectories. Prognostic factors have been identified and validated in patients with
cancer. These can be clinical markers or biomarkers. Clinical markers including weight
loss and Performance Status (PS), and biomarkers such as C-reactive protein (CRP),
lactate dehydrogenase (LDH), White cell count (WCC) and albumin, all representative
of systemic inflammation, have been shown to be predictive of survival. Several
prognostic factors have been combined to develop prognostic tools to improve
prognostication accuracy. The aims were to examine all these prognostic markers and
the tools, to clarify which prognostic markers are most predictive of survival in
advanced cancer.
METHODS:
To meet these aims a systematic review, an analysis of a prospectively
collected biobank of patients with lung cancer and finally a large de novo multi-centre
(UK) observational cohort study (Inflammatory biomarkers in Prognosis in Advanced
Cancer [IPAC] study), were undertaken. The latter examined prognostic factors and
was informed by the systematic review and biobank analysis. The prognostic factors
evaluated throughout included demographic factors, disease characteristics, clinical
factors and biomarkers. Literature appraisal and synthesis, survival analysis and
logistic regression methods were employed as appropriate.
RESULTS:
The systematic review concluded that numerous prognostic tools predict
survival in patients with advanced cancer; however comparison was difficult due to the
heterogeneity of the tools and the methods used to determine their accuracy. Some
tools incorporate prognostic factors that have been independently validated to be of
prognostic significance in advanced cancer whilst other tools may include some
factors which are not validated. The prognostic tools demonstrating greatest accuracy
in determining survival are the Palliative Performance Scale (PPS), the Palliative
Prognostic Score (PaP), the Palliative Prognostic Index (PPI), and the Glasgow
Prognostic Score (GPS) including the modified variant (mGPS). These tools have all
been externally validated in more than 2000 patients with advanced cancer and were
independently associated with survival (p<0.001).
The biobank analysis identified the markers (clinical and biomarkers) which are most
predictive of survival in advanced lung cancer. The prognostic markers included in
many of the prognostic tools with greatest survival prediction accuracy are PS and
mGPS (p<0.001).
A prospectively acquired biobank identified the markers (clinical and biomarkers)
which are most predictive of survival in advanced incurable lung cancer. The
prognostic markers which are included in many of the prognostic tools with greatest
survival prediction accuracy are PS and mGPS.
The prospective observational study demonstrated that CPS (Clinician Predicted
Survival), mGPS, ECOG-PS (Eastern Cooperative Oncology Group - Performance
Status), dyspnoea, Global Health, cognitive impairment, anorexia, weight loss, LDH,
WCC and neutrophil count (NC) predicted survival at 30 days (univariate analysis).
CPS, ECOG-PS, mGPS, dyspnoea, Global Health, cognitive impairment, anorexia,
weight loss, LDH, WCC and NC, predicted survival at 3 months. On multivariate
analysis, ECOG-PS, mGPS and neutrophil count predicted survival at 30 days while
ECOG-PS, mGPS, weight loss, LDH and WCC predicted survival at 3 months.
CONCLUSION:
In patients with advanced cancer, the most accurate prognostic factors
include clinical markers (Performance Status, weight loss) and biomarkers of the
systemic inflammatory response (CRP and albumin [combined in the mGPS], NC,
WCC). The next step in this work is assessing how these can be utilised in clinical
practice.
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dc.identifier.uri
http://hdl.handle.net/1842/35849
dc.language.iso
en
dc.publisher
The University of Edinburgh
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dc.relation.hasversion
Simmons CPL, McMillan DC, McWilliams K, et al. Prognostic Tools in Patients With Advanced Cancer: A Systematic Review. J Pain Symptom Manage. 2017;53(5):962-970 e910.
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dc.relation.hasversion
Simmons CP, Koinis F, Fallon MT, et al. Prognosis in advanced lung cancer-- A prospective study examining key clinicopathological factors. Lung Cancer. 2015;88(3):304-309.
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dc.subject
survival factors
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dc.subject
prognostic markers
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dc.subject
survival estimation
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dc.subject
statistics
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dc.subject
analysis
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dc.subject
Palliative Performance Scale
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dc.subject
Palliative Prognostic Score
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dc.subject
Palliative Prognostic Index
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dc.subject
Glasgow Prognostic Score
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dc.subject
Performance Status
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dc.subject
modified Glasgow Prognostic Score
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dc.subject
prognostic accuracy
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dc.title
Study of prognostic markers in advanced cancer
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
MD Doctor of Medicine
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