Objective To develop a novel prognostic indicator for use in patients with advanced cancer that is significantly better than clinicians' estimates of survival.Design Prospective multicentre observational cohort study.Setting 18 palliative care services in the UK (including hospices, hospital support teams, and community teams).Participants 1018 patients with locally advanced or metastatic cancer, no longer being treated for cancer, and recently referred to palliative care services. Main outcome measuresPerformance of a composite model to predict whether patients were likely to survive for "days" (0-13 days), "weeks" (14-55 days), or "months+" (>55 days), compared with actual survival and clinicians' predictions.Results On multivariate analysis, 11 core variables (pulse rate, general health status, mental test score, performance status, presence of anorexia, presence of any site of metastatic disease, presence of liver metastases, C reactive protein, white blood count, platelet count, and urea) independently predicted both two week and two month survival. Four variables had prognostic significance only for two week survival (dyspnoea, dysphagia, bone metastases, and alanine transaminase), and eight variables had prognostic significance only for two month survival (primary breast cancer, male genital cancer, tiredness, loss of weight, lymphocyte count, neutrophil count, alkaline phosphatase, and albumin). Separate prognostic models were created for patients without (PiPS-A) or with (PiPS-B) blood results. The area under the curve for all models varied between 0.79 and 0.86. Absolute agreement between actual survival and PiPS predictions was 57.3% (after correction for over-optimism). The median survival across the PiPS-A categories was 5, 33, and 92 days and survival across PiPS-B categories was 7, 32, and 100.5 days. All models performed as well as, or better than, clinicians' estimates of survival. ConclusionsIn patients with advanced cancer no longer being treated, a combination of clinical and laboratory variables can reliably predict two week and two month survival. IntroductionPatients with advanced cancer and their carers often wish to know how long they have left to live. 1 2 Accurate prognostic information can allow patients adequate time to prepare for their impending death. 3 Qualitative studies show that patients in palliative care want to be given honest and accurate prognostic information but that this information needs to be shared sensitively and in a way that respects patients' desire to maintain hope. 4 5 Prognostic information is also important for clinicians. Realistic survival estimates can inform decisions about the appropriateness of medical interventions and the timing of referral to specialist palliative care services or admission to a hospice. Clinicians' predictions are routinely used to prioritise patients who are suitable for inclusion in programmes such as the Gold Standards Framework, 6 to determine which patients RESEARCHare suitable for "fast-tracking" arrangements for ...

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BACKGROUND: Lymphoedema develops after axillary clearance (ANC) in 25% of patients. This prospective, multi-centre study compared multi-frequency bioimpedance spectroscopy (BIS) with arm volume measurement to: (1) determine which test has better diagnostic accuracy, (2) identify factors predicting development of lymphoedema, and its effect on quality-of-life. METHODS: Participants (N = 1100) underwent measurements pre and post-ANC surgery for breast cancer. Relative arm volume increase (RAVI) of >10% diagnosed lymphoedema. Predictors of lymphoedema were determined using logistic regression. Optimal diagnostic method was assessed using diagnostic accuracy. Quality-of-life was assessed using the FACT B + 4 questionnaire. RESULTS: Lymphoedema was diagnosed in 22.8% women using RAVI > 10%, 45.6% using BIS criteria, while 24.5% underwent compression sleeve application by 24 months. BMI > 30 was an independent factor for both development (p = 0.005) and progression (p = 0.015) of lymphoedema. RAVI at 1 month, BMI > 30 and number of involved nodes contributed to a novel scoring model to predict lymphoedema by 36 months. Larger decreases in QoL scores post-surgery occurred in lymphoedema patients (p < 0.001). Progression to moderate lymphoedema occurred in 15% patients after sleeve application. CONCLUSIONS: RAVI measurement was the best diagnostic tool for lymphoedema. BIS alone is not appropriate for lymphoedema screening or diagnosis. BMI > 30 predicted lymphoedema diagnosis and progression.

Phone : 0208 725 0957Fax : 0208 725 3444 Conflict of interestAll authors declare no conflict of interest. AcknowledgementsWe would like to acknowledge the members of the Lymphoedema Research Consortium, UK. We extend our thanks to the patients and their families and the British Heart Foundation for funding the work of KG (FS/11/40/28739) and PO (PG/10/58/28477). CGE-00117-2013Connell et al 2 AbstractHistorically, primary lymphoedema was classified into just three categories depending on the age of onset of swelling; congenital, praecox and tarda. Developments in clinical phenotyping and identification of the genetic cause of some of these conditions have demonstrated that primary lymphoedema is highly heterogenous. In 2010 we introduced a new classification and diagnostic pathway as a clinical and research tool. This algorithm has been used to delineate specific primary lymphoedema phenotypes, facilitating the discovery of new causative genes. This paper reviews the latest molecular findings and provides an updated version of the classification and diagnostic pathway based on this new knowledge. Keywords

Objective To develop a novel prognostic indicator for use in patients with advanced cancer that is significantly better than clinicians' estimates of survival.Design Prospective multicentre observational cohort study.Setting 18 palliative care services in the UK (including hospices, hospital support teams, and community teams).Participants 1018 patients with locally advanced or metastatic cancer, no longer being treated for cancer, and recently referred to palliative care services. Main outcome measuresPerformance of a composite model to predict whether patients were likely to survive for "days" (0-13 days), "weeks" (14-55 days), or "months+" (>55 days), compared with actual survival and clinicians' predictions.Results On multivariate analysis, 11 core variables (pulse rate, general health status, mental test score, performance status, presence of anorexia, presence of any site of metastatic disease, presence of liver metastases, C reactive protein, white blood count, platelet count, and urea) independently predicted both two week and two month survival. Four variables had prognostic significance only for two week survival (dyspnoea, dysphagia, bone metastases, and alanine transaminase), and eight variables had prognostic significance only for two month survival (primary breast cancer, male genital cancer, tiredness, loss of weight, lymphocyte count, neutrophil count, alkaline phosphatase, and albumin). Separate prognostic models were created for patients without (PiPS-A) or with (PiPS-B) blood results. The area under the curve for all models varied between 0.79 and 0.86. Absolute agreement between actual survival and PiPS predictions was 57.3% (after correction for over-optimism). The median survival across the PiPS-A categories was 5, 33, and 92 days and survival across PiPS-B categories was 7, 32, and 100.5 days. All models performed as well as, or better than, clinicians' estimates of survival. ConclusionsIn patients with advanced cancer no longer being treated, a combination of clinical and laboratory variables can reliably predict two week and two month survival. IntroductionPatients with advanced cancer and their carers often wish to know how long they have left to live. 1 2 Accurate prognostic information can allow patients adequate time to prepare for their impending death. 3 Qualitative studies show that patients in palliative care want to be given honest and accurate prognostic information but that this information needs to be shared sensitively and in a way that respects patients' desire to maintain hope. 4 5 Prognostic information is also important for clinicians. Realistic survival estimates can inform decisions about the appropriateness of medical interventions and the timing of referral to specialist palliative care services or admission to a hospice. Clinicians' predictions are routinely used to prioritise patients who are suitable for inclusion in programmes such as the Gold Standards Framework, 6 to determine which patients RESEARCHare suitable for "fast-tracking" arrangements for ...

Traditional classification systems for lymphoedema are of limited use for the diagnosis of specific forms of primary lymphoedema. The understanding of primary lymphoedema has been impeded by confusing terminology and a tendency to simply divide patients into three categories based on the age of onset: lymphoedema congenita manifests at or shortly after birth, lymphoedema praecox is apparent before the age of 35 years and lymphoedema tarda manifests thereafter. The clinical presentation in the spectrum of primary lymphoedema disorders is very variable; the phenotypes of primary lymphoedema conditions vary in the age of onset, site of the oedema, inheritance patterns, associated features and genetic causes. Different inheritance patterns are recognised and there are numerous associated anomalies. Some subgroups, such as Milroy disease and Lymphoedema distichiasis, are well characterised, but others are not. A new clinical classification for primary lymphoedema has been developed as a diagnostic algorithm. Its use is demonstrated on 333 probands referred to our lymphoedema clinic. Grouping patients by accurate phenotyping facilitates molecular investigations, understanding of inheritance patterns, and the natural history of different types of primary lymphoedema. Descriptions of the diagnostic categories, some of which have not been previously clearly defined as distinct clinical entities, are illustrated by clinical cases.

Primary lymphatic anomalies may present in a myriad of ways and are highly heterogenous. Careful consideration of the presentation can lead to an accurate clinical and/or molecular diagnosis which will assist with management. The most common presentation is lymphoedema, swelling resulting from failure of the peripheral lymphatic system. However, there may be internal lymphatic dysfunction, for example, chylous reflux, or lymphatic malformations, including the thorax or abdomen. A number of causal germline or postzygotic gene mutations have been discovered. Some through careful phenotyping and categorisation of the patients based on the St George’s classification pathway/algorithm. The St George’s classification algorithm is aimed at providing an accurate diagnosis for patients with lymphoedema based on age of onset, areas affected by swelling and associated clinical features. This has enabled the identification of new causative genes. This update brings the classification of primary lymphatic disorders in line with the International Society for the Study of Vascular Anomalies 2018 classification for vascular anomalies. The St George’s algorithm considers combined vascular malformations and primary lymphatic anomalies. It divides the types of primary lymphatic anomalies into lymphatic malformations and primary lymphoedema. It further divides the primary lymphoedema into syndromic, generalised lymphatic dysplasia with internal/systemic involvement, congenital-onset lymphoedema and late-onset lymphoedema. An audit and update of the algorithm has revealed where new genes have been discovered and that a molecular diagnosis was possible in 26% of all patients overall and 41% of those tested.

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.