Development of a score that predicts survival among patients with bone metastasis revealing solid tumor

Predictors of Mortality in Patients with Advanced Cancer-A Systematic Review and Meta-Analysis

To timely initiate advance care planning in patients with advanced cancer, physicians should identify patients with limited life expectancy. We aimed to identify predictors of mortality. To identify the relevant literature, we searched Embase, MEDLINE, Cochrane Central, Web of Science, and PubMed databases between January 2000-April 2020. Identified studies were assessed on risk-of-bias with a modified QUIPS tool. The main outcomes were predictors and prediction models of mortality within a period of 3-24 months. We included predictors that were studied in ≥2 cancer types in a meta-analysis using a fixed or random-effects model and summarized the discriminative ability of models. We included 68 studies (ranging from 42 to 66,112 patients), of which 24 were low risk-of-bias, and 39 were included in the meta-analysis. Using a fixed-effects model, the predictors of mortality were: the surprise question, performance status, cognitive impairment, (sub)cutaneous metastases, body mass index, comorbidity, serum albumin, and hemoglobin. Using a random-effects model, predictors were: disease stage IV (hazard ratio [HR] 7.58; 95% confidence interval [CI] 4.00-14.36), lung cancer (HR 2.51; 95% CI 1.24-5.06), ECOG performance status 1+ (HR 2.03; 95% CI 1.44-2.86) and 2+ (HR 4.06; 95% CI 2.36-6.98), age (HR 1.20; 95% CI 1.05-1.38), male sex (HR 1.24; 95% CI 1.14-1.36), and Charlson comorbidity score 3+ (HR 1.60; 95% CI 1.11-2.32). Thirteen studies reported on prediction models consisting of different sets of predictors with mostly moderate discriminative ability. To conclude, we identified reasonably accurate non-tumor specific predictors of mortality. Those predictors could guide in developing a more accurate prediction model and in selecting patients for advance care planning.

An easy tool to predict survival in patients receiving radiation therapy for painful bone metastases

PURPOSE

Patients with bone metastases have a widely varying survival. A reliable estimation of survival is needed for appropriate treatment strategies. Our goal was to assess the value of simple prognostic factors, namely, patient and tumor characteristics, Karnofsky performance status (KPS), and patient-reported scores of pain and quality of life, to predict survival in patients with painful bone metastases.

METHODS AND MATERIALS

In the Dutch Bone Metastasis Study, 1157 patients were treated with radiation therapy for painful bone metastases. At randomization, physicians determined the KPS; patients rated general health on a visual analogue scale (VAS-gh), valuation of life on a verbal rating scale (VRS-vl) and pain intensity. To assess the predictive value of the variables, we used multivariate Cox proportional hazard analyses and C-statistics for discriminative value. Of the final model, calibration was assessed. External validation was performed on a dataset of 934 patients who were treated with radiation therapy for vertebral metastases.

RESULTS

Patients had mainly breast (39%), prostate (23%), or lung cancer (25%). After a maximum of 142 weeks' follow-up, 74% of patients had died. The best predictive model included sex, primary tumor, visceral metastases, KPS, VAS-gh, and VRS-vl (C-statistic = 0.72, 95% CI = 0.70-0.74). A reduced model, with only KPS and primary tumor, showed comparable discriminative capacity (C-statistic = 0.71, 95% CI = 0.69-0.72). External validation showed a C-statistic of 0.72 (95% CI = 0.70-0.73). Calibration of the derivation and the validation dataset showed underestimation of survival.

CONCLUSION

In predicting survival in patients with painful bone metastases, KPS combined with primary tumor was comparable to a more complex model. Considering the amount of variables in complex models and the additional burden on patients, the simple model is preferred for daily use. In addition, a risk table for survival is provided.

Clinical, economic and humanistic burdens of skeletal-related events associated with bone metastases

Despite effective skeletal-related event (SRE)-limiting therapies such as zoledronic acid and denosumab, SREs continue to place a meaningful burden on patients, providers and payers. However, studies of SRE-related effects on clinical (i.e., survival), economic (i.e., cost per event) and humanistic (i.e., quality of life) outcomes often report results in a composite manner and frequently do not differentiate the effects by SRE-type (i.e., bone radiation, bone surgery, hypercalcemia, pathological fracture and spinal cord compression). Nevertheless, understanding the differential burdens of individual SRE types, which vary in severity and duration of effect, is an important consideration - particularly in pharmacoeconomic evaluations of SRE-limiting therapies. In this review of the clinical, economic and humanistic SRE burden, it was found that SRE types can be differentiated by these outcomes, although economic outcomes are far more frequently reported than clinical or humanistic.

Cancer-associated hypercalcaemia in squamous-cell malignancies: a survival and prognostic factor analysis

The aim of this study is to analyse survival and prognostic factors in patients diagnosed with squamous cell carcinoma (SCC) presenting a first episode of cancer-associated hypercalcaemia (CAH). Retrospectively, the authors reviewed data from 220 patients with biopsy proven SCC who presented a first episode of CAH. They were treated in a single centre between 1995 and 2007. The survival analyses were done using the Kaplan-Meier method and Cox analysis. The primary endpoint was the overall survival from the date of hypercalcaemia episode. Median age was 55 years. Median survival was 64 days (1-197). Three independent prognostic factors were identified: brain metastasis (hazard ratio (HR)=2.58 CI (1.03-6.45)), corrected calcaemia>3 mmol/l (HR=1.45 CI (1.05-2.01)) and hypoalbuminaemia (HR=1.48 CI (1.07-2.04)). Using these factors, the authors performed a bedside prognostic score. In conclusion, median survival in patients diagnosed with SCC and CAH is extremely poor. The bedside prognostic score that the authors developed can help to anticipate patients' prognosis and adapt the treatment. This score needs to be validated on an independent cohort.