Prognostic Implication of Body Mass Index on Survival Outcomes in Surgically Treated Nonmetastatic Renal Cell Carcinoma: A Single-Institutional Retrospective Analysis of a Large Cohort

Seon, Dong Young; Kwak, Cheol; Kim, Hyeon Hoe; Ku, Ja Hyeon; Kim, Hyung Suk

doi:10.1245/s10434-020-08417-6

Cited by 6 publications

(6 citation statements)

References 29 publications

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“…The co-morbidities of hypertension (P \ 0.001) and diabetes mellitus (P = 0.002) have a higher frequency in overweight and obese groups compared with those in the normal group. 7 Accordingly, an asymptomatic presentation at diagnosis was found to be highly associated with the obese patients group (P = 0.001) and pathologically nodal negative results were also highly associated with the obese patient group (P = 0.033). 7 Another important factor related to the outcome is treatment efficacy and resistance.…”

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confidence: 88%

“…7 Accordingly, an asymptomatic presentation at diagnosis was found to be highly associated with the obese patients group (P = 0.001) and pathologically nodal negative results were also highly associated with the obese patient group (P = 0.033). 7 Another important factor related to the outcome is treatment efficacy and resistance. This factor depends on the treatment agent and the results may alter from day to day.…”

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confidence: 88%

“…Overweight (P = 0.009) and obese (P = 0.009) patients in particular demonstrated better cancer-specific survival compared with the normal BMI patients. 7 They concluded that additional basic research is required to determine the biological mechanisms that explain the correlation between BMI and survival outcomes. 7 As described above, it is interesting that although obesity is a well-established risk factor for developing RCC, [1][2][3] RCC in obese patients is related to a relatively favorable outcome.…”

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confidence: 99%

“…7 They concluded that additional basic research is required to determine the biological mechanisms that explain the correlation between BMI and survival outcomes. 7 As described above, it is interesting that although obesity is a well-established risk factor for developing RCC, [1][2][3] RCC in obese patients is related to a relatively favorable outcome. [4][5][6] Previously, it was reported that a higher BMI was associated with a low Fuhrman grade in clinically localized renal masses, regardless of the tumor size, renal mass pathology, RCC subtype, or clinical stage.…”

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confidence: 99%

“…10,11 Although the study reported by Seon et al did not describe the precise treatment sequences for these patients, almost patients must be treated with tyrosine kinase inhibitors (TKIs). 7 Several studies also demonstrated that overweight and obese RCC patients showed longer post-operative survival compared with normal-weight patients in the cytokine and TKI era. [4][5][6][7] Currently, in the immune checkpoint inhibitor era, the risk factors and/or poor prognostic factors, including obesity and PD-L1 expression, that were identified before or in the TKI era, may be changing.…”

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confidence: 99%

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Editorial Comment On: Prognostic Implication of Body Mass Index on Survival Outcomes in Surgically-Treated Non-metastatic Renal Cell Carcinoma: A Single Institutional, Retrospective Analysis of a Large Cohort

Yuasa

2020

Ann Surg Oncol

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To date, various epidemiologic studies have consistently demonstrated a significant correlation between obesity and the risk of developing renal cell cancer (RCC). 1-3 Moreover, a large contemporary study also demonstrated that the obesity represents a risk factor for RCC-specific mortality. 3 However, many studies have shown that obesity is a favorable predictor of the survival outcome after surgical removal of localized RCC in clinical practice. 4-6 These phenomena are called the ''obesity paradox'' in which a higher body mass index (BMI) that is expected to contribute to worse oncological outcomes actually improves these outcomes. 5,6 However, most previous studies have originated from Western countries, 4-6 and the results for Asians may be different from those for Caucasians because there are some differences in body build, lifestyle, genetic background, and general circumstances. 7 In this issue of Annals of Surgical Oncology, Seon et al. showed that obese patients had relatively favorable survival outcomes after RCC surgery, using a relatively large Asian cohort. 7 The obese patients presented favorable 5-year recurrence-free (90.7% vs 84.9%, P \ 0.001), overall (91.8% vs 86.8%, P = 0.002), and cancer-specific (94.8% vs 89.4%, P = 0.002) survival rates compared with normal BMI patients. 7 A multivariate analysis also showed that an increasing BMI was an independent predictor of favorable survival outcomes (P \ 0.05 for all). 7

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confidence: 88%

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confidence: 88%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Editorial Comment On: Prognostic Implication of Body Mass Index on Survival Outcomes in Surgically-Treated Non-metastatic Renal Cell Carcinoma: A Single Institutional, Retrospective Analysis of a Large Cohort

Yuasa

2020

Ann Surg Oncol

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Fatty acid metabolism reprogramming in ccRCC: mechanisms and potential targets

et al. 2022

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Recurrence prediction in clear cell renal cell carcinoma using machine learning of quantitative nuclear features

Matsubara

Saito

Tokuyama

et al. 2023

Sci Rep

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The recurrence of non-metastatic renal cell carcinoma (RCC) may occur early or late after surgery. This study aimed to develop a recurrence prediction machine learning model based on quantitative nuclear morphologic features of clear cell RCC (ccRCC). We investigated 131 ccRCC patients who underwent nephrectomy (T1-3N0M0). Forty had recurrence within 5 years and 22 between 5 and 10 years; thirty-seven were recurrence-free during 5–10 years and 32 were for more than 10 years. We extracted nuclear features from regions of interest (ROIs) using a digital pathology technique and used them to train 5- and 10-year Support Vector Machine models for recurrence prediction. The models predicted recurrence at 5/10 years after surgery with accuracies of 86.4%/74.1% for each ROI and 100%/100% for each case, respectively. By combining the two models, the accuracy of the recurrence prediction within 5 years was 100%. However, recurrence between 5 and 10 years was correctly predicted for only 5 of the 12 test cases. The machine learning models showed good accuracy for recurrence prediction within 5 years after surgery and may be useful for the design of follow-up protocols and patient selection for adjuvant therapy.

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Prognostic Implication of Body Mass Index on Survival Outcomes in Surgically Treated Nonmetastatic Renal Cell Carcinoma: A Single-Institutional Retrospective Analysis of a Large Cohort

Cited by 6 publications

References 29 publications

Editorial Comment On: Prognostic Implication of Body Mass Index on Survival Outcomes in Surgically-Treated Non-metastatic Renal Cell Carcinoma: A Single Institutional, Retrospective Analysis of a Large Cohort

Editorial Comment On: Prognostic Implication of Body Mass Index on Survival Outcomes in Surgically-Treated Non-metastatic Renal Cell Carcinoma: A Single Institutional, Retrospective Analysis of a Large Cohort

Fatty acid metabolism reprogramming in ccRCC: mechanisms and potential targets

Recurrence prediction in clear cell renal cell carcinoma using machine learning of quantitative nuclear features

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