Personalized Palliative and Survivorship Care for Patients With Metastatic Cancer Treated With Radiation Therapy.

While the benefits of early palliative care for patients with metastatic cancer are well established, cancer survivorship remains inadequately integrated into the care of patients with distant metastases. Moreover, the optimal model of care delivery is poorly defined. A prognostic model previously developed and validated at Good Samaritan University Hospital identified four groups of patients with metastatic solid tumor malignancy having very favorable, favorable, standard or unfavorable prognoses with median survival of 31, 14, 4 and 1 month, respectively. This framework holds promise for the personalized delivery of supportive, palliative and survivorship care services in the context of radiation therapy. We review the published literature providing the rationale for a novel multidisciplinary care model where the radiation oncology Clinical Nurse Specialist identifies and coordinates interventions to address unmet physical and emotional issues faced by survivors with metastatic cancer with the goal of improving quality of life and overall survival.

Association of radiation dose intensity with overall survival in patients with distant metastases.

BACKGROUND: Patients with metastatic cancer referred to radiation oncology have diverse prognoses and there is significant interest in personalizing treatment. We hypothesized that patients selected for higher biologically equivalent doses have improved overall survival. METHODS: The study population consists of 355 consecutive adult patients with distant metastases treated by a single radiation oncologist from 2014 to 2018. The validated NEAT model was used to prospectively stratify patients into four distinct cohorts. Radiation dose intensity was standardized using the equivalent dose in 2 Gy fractions (EQD2) model with an α/ß of 10. Radiation dose intensity on survival was assessed via Cox regression models and propensity score match pairing with Kaplan-Meier analysis. RESULTS: The median survival was 9.3 months and the median follow-up for surviving patients was 18.3 months. The NEAT model cohorts indicated median survivals of 29.5, 11.8, 4.9, and 1.8 months. Patients receiving an EQD2 of ≥40 Gy had a median survival of 16.0 months versus 3.8 months for patients receiving an EQD2 of <40 Gy (p < 0.001). On multivariable analysis, performance status, primary tumor site, radiation dose intensity, albumin, liver metastases, and number of active tumors were all independent predictors of survival (p < 0.05 for all). Propensity score matching was performed for performance status, albumin, number of active tumors, primary tumor site, and liver metastasis, finding higher EQD2 to remain significantly associated with improved survival within the matched cohort (p = 0.004). CONCLUSION: Higher radiation dose intensity was used in patients with better prognosis and was associated with improved survival for patients with metastatic disease.

Correction: Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology.

[This corrects the article DOI: 10.1371/journal.pone.0124329.].

Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology.

BACKGROUND: There is an urgent need for a robust, clinically useful predictive model for survival in a heterogeneous group of patients with metastatic cancer referred to radiation oncology. METHODS: From May 2012 to August 2013, 143 consecutive patients with stage IV cancer were prospectively evaluated by a single radiation oncologist. We retrospectively analyzed the effect of 29 patient, laboratory and tumor-related prognostic factors on overall survival using univariate analysis. Variables that were statistically significant on univariate analysis were entered into a multivariable Cox regression to identify independent predictors of overall survival. RESULTS: The median overall survival was 5.5 months. Four prognostic factors significantly predicted survival on multivariable analysis including ECOG performance status (0-1 vs. 2 vs. 3-4), number of active tumors (1 to 5 vs. ≥ 6), albumin levels (≥ 3.4 vs. 2.4 to 3.3 vs. < 2.4 and primary tumor site (Breast, Kidney or Prostate vs. Other). Risk group stratification was performed by assigning points for adverse prognostic factors resulting in very low, low, intermediate and high risk groups. The median survival was > 31.4 months for very low risk patients compared to 14.5 months for low risk, 4.1 months for intermediate risk and 1.2 months for high risk (p < 0.001). CONCLUSIONS: These data suggest that a model that considers performance status, extent of disease, primary tumor site and serum albumin represents a simple model to accurately predict survival for patients with stage IV cancer who are potential candidates for radiation therapy.