Original Research

Onodera’s Prognostic Nutritional Index in soft tissue sarcoma patients as a predictor of wound complications


Background The ability to predict a wound complication after radiation therapy and surgery for soft tissue sarcomas remains difficult. Preoperative nutritional status, as determined by Onodera’s Prognostic Nutritional Index (OPNI), has been a predictor of complications in patients undergoing gastrointestinal surgery. However, the role OPNI has in predicting wound complications for soft tissue sarcoma remains unknown.

Objective To evaluate the role OPNI has in predicting wound complication in patients treated with radiation and surgery for soft tissue sarcomas.

Methods OPNI was calculated based on the published formula OPNI = (10*albumin level [g/dL]) + (0.005*total lymphocyte count). The albumin level and total lymphocyte counts closest to the index operation were chosen. Major and minor wound complications were identified. A receiver operating curve was calculated to identify a cut-off point value for OPNI and for age based on the best combination of sensitivity and specificity.

Results 44 patients were included in the study. Patients with an OPNI of <45.4 had a 7.5-times increased risk of a wound complication (P = .005; 95% confidence interval [CI], 1.8-31.0). An OPNI of <45.4 had a sensitivity of 62% and specificity of 82% of predicting a wound complication. Being older than 73 years was associated with a 6.8-times increased risk of wound complications (P = .01; 95% CI, 1.6-28.7).

Limitations Small sample size for patients with a rare condition

Conclusion An OPNI of <45.4 and being older than 73 years are strong predictors of which patients will have a wound complication after radiation therapy for soft tissue sarcomas. Preoperative nutritional status could be an important modifiable factor to help decrease wound complications.

Wound complications after pre- or post-operative radiation for soft tissue sarcomas are well established.1 The ability to predict who will have a wound complication remains difficult. Some studies have looked at risk factors such as smoking, and the preoperative nutritional status of patients has been identified as a risk factor for wound complication in patients with elective orthopedic surgical procedures.2 One validated method of measuring preoperative nutritional status in patients with gastrointestinal malignant tumors has been with Onodera’s Prognostic Nutritional Index (OPNI). It uses the patient’s preoperative albumin (g/dL) and absolute lymphocyte values (per mm3). The prognostic value of the OPNI has been demonstrated in patients with colorectal, esophageal, and gastric cancers, and has been shown to be prognostic for postoperative wound healing and overall prognosis.3-5 In this study, we investigate the significance of preoperative nutritional status, measured by OPNI, as a predictor of wound complications in patients treated with pre- or postoperative radiation for soft tissue sarcoma.


After receiving Institutional Review Board approval for the study, we conducted a retrospective review of consecutive patients treated during July 2012-April 2016 for a soft tissue sarcoma by the orthopedic oncology division at Cooper University Hospital in Camden, New Jersey. Inclusion criteria were patients with biopsy-proven soft tissue sarcoma, who were older than 18 years, had received pre- or postoperative radiation, and who had a recorded preoperative albumin and total lymphocyte count. A minimum follow-up of 3 months was required to assess for postoperative wound complications. Exclusion criteria included patients who had a bone sarcoma, had not received radiation therapy, or had a missing preoperative albumin or total lymphocyte count.

All of the surgeries were performed by 2 fellowshiptrained orthopedic oncologists. Patients received either pre- or postoperative radiation therapy by multiple radiation oncologists.

The OPNI was calculated based on the published formula OPNI = (10*albumin level [g/dL]) + (0.005*total lymphocyte count [per mm3]). The albumin level and total lymphocyte counts closest to the index operation were chosen.

Demographic information including gender, age at diagnosis, height, and weight were recorded. Data related to the patients’ pathologic diagnosis, stage at presentation, radiation therapy, and surgical resection were collected. A minor wound complication was defined as a wound problem that did not require operative intervention. Major wound complication was defined as a complication requiring operative intervention with or without flap reconstruction. Wound complications occurring within the 3-month postoperative period were considered.

Univariate and multiple variable analysis was performed. A P value <.05 was considered significant. A receiver operating curve as well as recursive partitioning was performed for OPNI and age to determine the best cut-off point to use in the analysis. The Sobel test was used to evaluate mediation. All statistical analysis was performed using SAS v9.4 and JMP10. (SAS Institute, Cary, NC).


In all, 44 patients (28 men, 16 women) were included in the study. Their mean age was 61.2 years (range, 19-94). The average size of the tumors was 8.5 cm in greatest dimension (range, 1.2-27.4 cm), and all of the patients had nonmetastatic disease at the time of surgical resection; 37 patients had R0 resections, and 7 patients had a positive margin from an outside hospital, but obtained R0 resections on a subsequent resection (Table 1 and Table 2). In all, 30 patients received preoperative radiation, 14 patients received postoperative radiation, 32 patients received external beam radiation, 8 received Cyberknife treatment, and information for 4 patients was not unavailable. Mean preoperative external beam radiation and Cyberknife dose was 4,931 Gy and 3,750 Gy, respectively. Mean postoperative external beam and Cyberknife radiation dose was 6,077 Gy and 4,000 Gy, respectively. When evaluating radiation dose delivered between those who had wound complications and those who did not, there was no significant difference (Table 3).