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. 2016 Jun;23(6):1803-14.
doi: 10.1245/s10434-015-4939-8. Epub 2015 Nov 9.

Factors Associated with Short-Term Mortality After Surgical Oncologic Emergencies

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Factors Associated with Short-Term Mortality After Surgical Oncologic Emergencies

Marianne R F Bosscher et al. Ann Surg Oncol. 2016 Jun.

Abstract

Background: The clinical outcome of patients with oncologic emergencies is often poor and mortality is high. It is important to determine which patients may benefit from invasive treatment, and for whom conservative treatment and/or palliative care would be appropriate. In this study, prognostic factors for clinical outcome are identified in order to facilitate the decision-making process for patients with surgical oncologic emergencies.

Methods: This was a prospective registration study for patients over 18 years of age, who were consulted for surgical oncologic emergencies between November 2013 and April 2014. Multiple variables were registered upon emergency consultation, and the follow-up period was 90 days. Multivariate logistic regression analysis was performed to identify factors associated with 30- and 90-day mortality.

Results: During the study period, 207 patients experienced surgical oncologic emergencies-101 (48.8 %) men and 106 (51.2 %) women, with a median age of 64 years (range 19-92). The 30-day mortality was 12.6 % and 90-day mortality was 21.7 %. Factors significantly associated with 30-day mortality were palliative intent of cancer treatment prior to emergency consultation (p = 0.006), Eastern Cooperative Oncology Group performance score (ECOG-PS) >0 (p for trend: p = 0.03), and raised lactate dehydrogenase (LDH) (p < 0.001). Additional factors associated with 90-day mortality were low handgrip strength (HGS) (p = 0.01) and low albumin (p = 0.002).

Conclusions: Defining the intent of prior cancer treatment and the ECOG-PS are of prognostic value when deciding on treatment for patients with surgical oncologic emergencies. Additional measurements of HGS, LDH, and albumin levels can serve as objective parameters to support the clinical assessment of individual prognosis.

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Figures

Fig. 1
Fig. 1
Kaplan–Meier plot for survival of patients with surgical oncologic emergencies, according to the classification of diagnosis, for the classifications with the largest 90-day mortality

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