Association of subcutaneous and visceral adipose tissue with overall survival in Taiwanese patients with bone metastases - results from a retrospective analysis of consecutively collected data.

BACKGROUND: Growing evidence indicates that measures of body composition may be related to clinical outcomes in patients with malignancies. The aim of this study was to investigate whether measures of regional adiposity-including subcutaneous adipose tissue index (SATI) and visceral adipose tissue index (VATI)-can be associated with overall survival (OS) in Taiwanese patients with bone metastases.
METHODS: This is a retrospective analysis of prospectively collected data. We examined 1280 patients with bone metastases who had undergone radiotherapy (RT) between March 2005 and August 2013. Body composition (SATI, VATI, and muscle index) was assessed by computed tomography at the third lumbar vertebra and normalized for patient height. Patients were divided into low- and high-adiposity groups (for both SATI and VATI) according to sex-specific median values.
RESULTS: Both SATI (hazard ratio [HR]: 0.696; P<0.001) and VATI (HR: 0.87; P = 0.037)-but not muscle index-were independently associated with a more favorable OS, with the former showing a stronger relationship. The most favorable OS was observed in women with high SATI (11.21 months; 95% confidence interval: 9.434-12.988; P<0.001).
CONCLUSIONS: High SATI and VATI are associated with a more favorable OS in Taiwanese patients with bone metastases referred for RT. The question as to whether clinical measures aimed at improving adiposity may improve OS in this clinical population deserves further scrutiny.

Introduction

Bone represents one of the most common sites for cancer spread, especially in patients with breast, prostate, or lung malignancies.[1, 2] Bone metastases are a significant source of morbidity, decreased performance status, and impaired quality of life. Moreover, the presence of bone metastases typically portends a poor prognosis, with a median overall survival (OS) of 6−7 months.[3]

Several factors–including clinical stage, patient demographics, and tumor histology–have been shown to affect the OS of patients with bone metastases.[4] Notably, sex disparities have been reported in the survival of patients with metastatic spread to the bone–with mortality rate ratios being significantly higher in males than in females for most malignancies.[5] Women also have a higher total adiposity than men, with a preponderance of subcutaneous adipose tissue. In contrast, men typically tend to accumulate visceral adipose tissue.[6] Subcutaneous and visceral adipose tissue indices (SATI and VATI, respectively) may influence the clinical outcomes of patients with cancer in a sex-dependent manner. [7]

Previous studies have reported a significant prognostic impact of SATI and VATI in different solid tumors, including advanced renal cell carcinoma, hepatocellular carcinoma, and pancreatic cancer,[8-10] although there has been some discrepant findings and the therapeutic implications of these observations have not been fully elucidated [11].

The aim of this study was to investigate whether measures of regional adiposity–including SATI and VATI–can be associated with overall survival (OS) in Taiwanese patients with bone metastases who were referred for radiotherapy (RT).

Materials and methods

Study patients

The present study was designed as a retrospective review of prospectively collected data and was conducted in a radiation oncology setting. Between March 2005 and August 2013, a total of 1654 Taiwanese patients with bone metastases were consecutively referred for RT to the Chang Gung Memorial Hospital. All of them had a histology-proven diagnosis of cancer and underwent computed tomography (CT) imaging within 30 days of the initial assessment. The diagnosis of bone metastases was based on the results of bone scintigraphy, X-ray, CT, or magnetic resonance imaging. Patients were excluded in presence of the following criteria: age <18 years, unavailable CT scans within two weeks before the start of RT, or lack of measures of weight and height within two weeks of enrolment. A total of 374 cases met the exclusion criteria, resulting in a final study sample of 1280 patients. The study protocol was reviewed and approved by the Institution Review Board of the Chang Gung Memorial Hospital (approval number: IRB: 201701224B0). Owing to the retrospective nature of the analysis, the need for informed consent was waived. Data collection from electronic medical records was supervised by an experienced nurse and a radiation oncologist.

CT-based body composition analysis

In keeping with previous methodology,[12] single-slice CT imaging at level L3 was used to analyze adiposity. SATI and VATI were identified according to Hounsfield units (HU) (from -190 to -30 HU for SATI and from -29 to 150 HU for VATI, respectively). The tissue cross-sectional areas (expressed in cm2) were calculated automatically by the CT software after normalization for patient height. SATI, VATI, total adipose tissue, and skeletal muscle indexes were expressed in cm2 m-2. All adiposity measures were taken in the two weeks preceding the start of RT.

Variable definition

Owing to the lack of a commonly accepted standard, SATI, VATI, and skeletal muscle indices were dichotomized according to median values measured at L3. OS was defined as the time elapsed from the start of RT for bone metastases to the date of death. Body mass index (BMI) was categorized as follows: underweight (BMI <18.5 kg/m2), normal weight (BMI: 18.5–24.99 kg/m2), overweight (BMI: 25–29.99 kg/m2), and obese (BMI ≥30 kg/m2). Equivalent doses in 2-Gy fraction (EQD2Gy) were used to express different total radiation doses in terms of amount and number of fractions. The time to metastases (calculated from the time of diagnosis of primary cancer to the identification of distant metastases) was categorized in ≤ 1 year versus >1 year. Metastases were considered multiple in presence of simultaneous involvement of at least two organs or different parts of skeleton (e.g., sternum and sacrum). The use of systemic therapy was investigated in the timeframe ranging from 1 month before RT to the date of the last follow-up. Other variables of interest were previously described.[13] The presence of comorbidities was dichotomized (yes versus no) according to the Charlson comorbidity index. Employment status was classified into three categories using the Registrar General’s Social Class (RGSC) scheme, as follows: unemployed, low-wage employed, and high-wage employed. Education status was categorized as high versus low (junior high school and above versus elementary school and below). The patient’s place of residence was dichotomized as either rural or urban (population density below or above 800 persons per km2, respectively). Risky oral habits were classified as follows: cigarette smoking (smoked ≥100 in lifetime versus < 100 cigarettes in lifetime and no current smoking), betel quid chewing (current/former versus never), and alcohol drinking (current/former versus never).

Statistical analysis

Continuous variables were compared using the Student’s t-test, whereas the Pearson’s chi-square test was used for categorical variables. The associations between the study variables (including indices of adiposity) and OS were investigated using univariate and multivariate Cox proportional hazard ratio analyses. Results were expressed as hazard ratios (HRs) with their 95% confidence interval (CIs). We also categorized patients according to SATI and VATI values (high versus low, with high values serving as references). Survival plots were constructed with the Kaplan-Meier method (log-rank test).Two-tailed P values <0.05 were considered statistically significant. Owing to the exploratory nature of the study, the Bonferroni’s correction was not applied.

Results

Patient characteristics

The general characteristics of the study patients are summarized in Table 1. Of the 1280 participants, 1237 were followed up until death, whereas the remaining 43 were censored on the date last known to be alive. The study cohort included 740 (57.8%) men and 540 (42.2%) women. The most common primary cancer site was the lung (35% in both sexes), and there were 897 (70%) patients with an ECOG performance status of 0−1. The interval between the diagnosis of primary cancer and the detection of metastases was 0.11 months in women (95% CI: 0−15.64 months) and 0.04 months (95% CI: 0−13.50 months) in men, respectively. Table 1 shows the results pertaining to adiposity indices. Men had higher skeletal muscle and VATI than women, whereas SATI was higher in women.

Table 1

Patient characteristics according to the subcutaneous and visceral adiposity status.

		SATI				VATI
		Low	High	Total number	P value	Low	High	Total number	P value
Number of patients		640 (50.0%)	640 (50.0%)	1280 (100%)		640 (50.0%)	640 (50.0%)	1280 (100%)
SATI
	Low					455 (71.1%)	185 (28.9%)	640 (50.0%)	<0.001a
	High					185 (28.9%)	455 (71.1%)	640 (50.0%)
	Median	8.15 (0.01–15.48)	27.77 (15.50–148.77)	15.49 (0.01–148.77)	<0.001b	9.93 (0.01–71.92)	23.30 (1.24–148.77)	15.49 (0.01–148.77)	<0.001b
	Mean ± SD, cm2/m2	7.96±4.58	33.42±17.87	20.69±18.22		12.81±11.92	28.57±19.96	20.69±18.22
VATI
	Low	455 (71.1%)	185 (28.9%)	640 (50.0%)	<0.001a
	High	185 (28.9%)	455 (71.1%)	640 (50.05%)
	Median	4.74 (0.02–72.53)	15.59 (0.40–93.34)	9.84 (0.02–93.34)	<0.001b	3.70 (0.02–9.83)	19.35 (9.84–93.34)	9.84 (0.02–93.34)	<0.001b
	Mean	8.10±9.39	18.35±13.19	13.23±12.54		4.07±2.92	22.39±11.75	13.23±12.54
Muscle index
	Low	293 (45.8%)	347 (54.2%)	640 (50.0%)	0.003a	333 (52.0%)	307 (48.0%)	640 (50.0%)	0.162a
	High	347 (54.2%)	293 (45.8%)	640 (50.0%)		307 (48.0%)	333 (52.0%)	640 (50.0%)
	Median	17.23 (4.02–49.49)	16.01 (6.44–93.90)	16.61 (4.02–93.90)	0.015b	16.41 (4.02–43.93)	16.89 (6.44–93.90)	16.61 (4.02–93.9)	0.063b
	Mean	17.78±5.59	16.96±6.28	17.37±5.95		17.06±5.65	17.68±6.23	17.37±5.95
Age group, years
	<59.5	318 (49.7%)	313 (48.9%)	631 (49.3%)	0.823a	376 (58.8%)	255 (39.8%)	631 (49.3%)	<0.001a
	≥59.5	322 (50.3%)	327 (51.1%)	649 (50.7%)		264 (41.3%)	385 (60.2%)	649 (50.7%)
	Median	59.67 (19.54–95.57)	59.83 (21.98–87.05)	59.73 (19.54–95.57)	0.503b	56. 79 (19.54–95.57)	63.01 (27.9–90.45)	59.73 (19.54–95.57)	<0.001b
	Mean	60.55±13.16	60.08±12.11	60.32±12.64		57.59±12.94	63.04±11.73	60.32±12.64
Sex
	Female	152 (23.8%)	388 (60.6%)	540 (42.2%)	<0.001a	287 (44.8%)	253 (39.5%)	540 (42.2%)	0.062a
	Male	488 (76.3%)	252 (39.4%)	740 (57.8%)		353 (55.2%)	387 (60.5%)	740 (57.8%)
Performance status
	ECOG 0–1	428 (66.9%)	469 (73.3%)	897 (70.1%)	0.015a	444 (69.4%)	453 (70.8%)	897 (70.1%)	0.625a
	ECOG 2–4	212 (33.1%)	171 (26.7%)	383 (29.9%)		196 (30.6%)	187 (29.2%)	383 (29.9%)
Onset of metastasis
	≤ 1 year	470 (73.4%)	430 (67.2%)	900 (70.3%)	0.017a	455 (71.1%)	445 (69.5%)	900 (70.3%)	0.541a
	> 1 years	170 (26.6%)	210 (32.8%)	380 (29.7%)		185 (28.9%)	195 (30/5%)	380 (29.7%)
	Median	0.08 (0–13.50)	0.04 (0–15.64)	0.05 (0–15.64)	0.006b	0.08 (0–15.64)	0.04 (0–15.64)	0.05 (0–15.64)	0.652b
	Mean	1.04±2.03	1.40±2.56	1.22±2.32		1.19±2.28	1.25±2.36	1.22±2.32
Site of metastasis
	Bone	543 (84.8%)	542 (84.7%)	1085 (84.8%)	0.943	524 (81.9%)	561 (87.7%)	1085 (84.8%)	0.007
	Brain	17 (2.7%)	19 (3.0%)	36 (2.8%)		25 (3.9%)	11 (1.7%)	36 (2.8%)
	Others	80 (12.5%)	79 (12.3%)	159 (12.4%)		91 (14.2%)	68 (10.6%)	159 (12.4%)
Multiple metastases
	No	121 (18.9%)	124 (19.4%)	245 (19.1%)	0.832a	120 (18.8%)	125 (19.5%)	245 (19.1%)	0.776a
	Yes	519 (81.1%)	516 (80.6%)	1035 (80.9%)		520 (81.3%)	515 (80.5%)	1035 (80.9%)
Site of primary cancer
	Lung cancer	253 (39.5%)	222 (34.7%)	475 (37.1%)	<0.001a	232 (36.3%)	243 (38.0%)	475 (37.1%)	<0.001a
	Hepatoma	75 (11.7%)	60 (9.4%)	135 (10.5%)		75 (11.7%)	60 (9.4%)	135 (10.5%)
	Breast cancer	26 (4.1%)	90 (14.1%)	116 (9.1%)		56 (8.8%)	60 (9.4%)	116 (9.1%)
	Prostate cancer	39 (6.1%)	53 (8.3%)	92 (7.2%)		21 (3.3%)	71 (11.1%)	92 (7.2%)
	Rectal cancer	34 (5.3%)	43 (6.7%)	77 (6.0%)		40 (6.3%)	37 (5.8%)	77 (6.0%)
	Others	213 (33.3%)	172 (26.9%)	385 (30.1%)		216 (33.8%)	169 (26.4%)	385 (30.1%)
EQD2Gy
	<32.5	337 (52.7%)	279 (43.6%)	616 (48.1%)	0.001a	325 (50.8%)	291 (45.5%)	616 (48.1%)	0.065a
	≥32.5	303 (47.3%)	361 (56.4%)	664 (51.9%)		315 (49.2%)	349 (54.5%)	664 (51.9%)
	Median	31.25 (1.44–70.00)	32.50 (3.25–84.00)	32.50 (1.44–84.00)	<0.001b	31.98 (1.83–70.00)	32.50 (1.44–84.00)	32.50 (1.44–84.00)	0.484b
	Mean	28.14±10.99	30.66±10.70	29.40±10.91		29.19±11.29	29.62±10.52	29.40±10.91
Systemic therapy
	No	266 (41.6%)	164 (25.6%)	430 (33.6%)	<0.001a	238 (37.2%)	192 (30.0%)	430 (33.6%)	0.008a
	Yes	374 (58.4%)	476 (74.4%)	850 (66.4%)		402 (62.8%)	448 (70.0%)	850 (66.4%)
Comorbidities
	No	296 (46.3%)	256 (40.0%)	552 (43.1%)	0.028a	328 (51.2%)	224 (35.0%)	552 (43.1%)	<0.001a
	Yes	344 (53.8%)	384 (60.0%)	728 (56.9%)		312 (48.8%)	416 (65.0%)	728 (56.9%)
Employment status
	High	152 (23.8%)	142 (22.2%)	294 (23.0%)	<0.001a	152 (23.8%)	142 (22.2%)	294 (23.0%)	0.152a
	Low	275 (43.0%)	169 (26.4%)	444 (34.7%)		234 (36.6%)	210 (32.8%)	444 (34.7%)
	None	213 (33.3%)	329 (51.4%)	542 (42.3%)		254 (39.7%)	288 (45.0%)	542 (42.3%)
Education level
	None/primary school	311 (48.6%)	344 (53.8%)	655 (51.2%)	0.074a	291 (45.5%)	364 (56.9%)	655 (51.2%)	<0.001a
	High school	329 (51.4%)	296 (46.3%)	625 (48.8%)		349 (54.5%)	276 (43.1%)	625 (48.8%)
Place of residence
	Urban	351 (54.8%)	345 (53.9%)	696 (54.4%)	0.779a	364 (56.9%)	332 (51.9%)	696 (54.4%)	0.082a
	Rural	289 (45.2%)	295 (46.1%)	584 (45.6%)		276 (43.1%)	308 (48.1%)	584 (45.6%)
Cigarette smoking
	No	270 (42.2%)	455 (71.1%)	725(56.6%)	<0.001a	356 (55.6%)	369 (57.7%)	725 (56.6%)	0.499a
	Yes	370 (57.8%)	185(28.9%)	555 (43.4%)		284 (44.4%)	271 (42.3%)	555 (43.4%)
Betel quid chewing
	No	511 (79.8%)	578 (90.3%)	1089 (85.1%)	<0.001a	538 (84.1%)	551 (86.1%)	1089 (85.1%)	0.347a
	Yes	129 (20.2%)	62 (9.7%)	191 (14.9%)		102 (15.9%)	89 (13.9%)	191 (14.9%)
Alcohol drinking
	No	420 (65.6%)	531 (83.0%)	951 (74.3%)	<0.001a	468 (73.1%)	483 (75.5%)	951 (74.3%)	0.338a
	Yes	220 (34.4%)	109 (17.0%)	329 (25.7%)		172 (26.9%)	157 (24.5%)	329 (25.7%)
Days of metastases treatment
	≤12	360 (56.3%)	311 (48.6%)	671 (52.4%)	0.007a	328 (51.2%)	343 (53.6%)	671 (52.4%)	0.433b
	≥13	280 (43.8%)	329 (51.4%)	609 (47.6%)		312 (48.8%)	297 (46.4%)	609 (47.6%)
	Median	11.50 (1–93)	13.00(1–67)	12.00(1–93)	<0.001b	12.00 (1–93)	12.00(1–67)	12.00(1–93)	0.984b
	Mean	11.60±7.98	13.59 ±8.86	12.59±8.49		12.59±8.91	12.60±8.05	12.59±8.49
Metastasis treatment period
	≤2009	331 (51.7%)	298 (46.6%)	629 (49.1%)	0.074a	312 (48.8%)	317 (49.5%)	629 (49.1%)	0.823a
	≥2010	309 (48.3%)	342 (53.4%)	651 (50.9%)		328 (51.2%)	323 (50.5)	651 (50.9%)
Body mass index, kg/m2
	Underweight	116 (18.1%)	4 (0.6%)	120 (9.4%)	<0.001a	118 (18.4%)	2 (0.3%)	120 (9.4%)	<0.001a
	Normal weight	478 (74.7%)	344 (53.8%)	822 (64.2%)		465 (72.7%)	357 (55.8%)	822 (64.2%)
	Overweight	45 (7.0%)	242 (37.8%)	287 (22.4%)		55 (8.6%)	232 (36.3%)	287 (22.4%)
	Obese	1 (0.2%)	50 (7.9%)	51 (4.0%)		2 (0.3%)	49 (7.7%)	51 (4.0%)
	Median	21.01 (13.34–20.65)	24.78 (16.98–38.73)	22.86 (13.34–38.73)	<0.001b	21.01 (13.34–30.65)	24.68 (16.98–38.73)	22.86 (13.34–38.73)	<0.001b
	Mean	21.12±2.74	25.08±3.32	23.10±3.63		21.12±2.74	25.08±3.32	23.10± 3.63

Abbreviations: SD, standard deviation; ECOG, Eastern Cooperative Oncology Group; EQD2 Gy, equivalent doses in 2-Gy fractions; SATI, subcutaneous adipose tissue index; VATI, visceral adipose tissue index.

aChi-square test

bANOVA test

Survival analysis

The median follow-up time for the 43 surviving patients was 78.28 months (range: 0.789−147.25 months). The median OS after RT was 6.03 months (range: 0.03−147.25 months). The 6-, 12-, 24-, and 48-month OS rates in women and men were 41.4%/61.8%, 23.6% /43.2%, 9.8%/22.6%, and 3.8%/11.2%, respectively. The median OS was 9.53 months (range: 0.10−137.42 months) in women and 4.7 months (range: 0.30−147.25) in men.

SATI values ≥11.63 cm2 in men and ≥25.21 cm2 in women were considered as high. Similarly, VATI values ≥10.46 cm2 in men and ≥8.96 cm2 in women were regarded as elevated. The median OS in the high and low SATI groups was 27.77 months (range: 15.50−148.77 months) and 8.15 months (range: 0.01−15.48 months), respectively. The median OS in the high and low VATI groups was 19.35 months (range: 9.84−93.34 months) and 3.70 months (range: 0.02−9.83 months), respectively.

The results of univariate and multivariate analyses are presented in Table 2. The following variables were independently associated with OS in multivariate analysis: SATI, VATI, sex, performance status, primary tumor site, more than one metastatic site, ECOG performance status, EQD2Gy, systemic therapy, education, days of metastases treatment, and time to metastases (Table 2).

Table 2

Univariate and multivariate analysis of overall survival.

		Univariate analysis		Multivariable analysis
		Overall survival		Overall survival
Number of patients = 1280		HR (95% CI)	P value	HR (95% CI)	P value
SATI (high versus low)		0.551 (0.492–0.618)	<0.001	0.696 (0.606–0.800)	<0.001
VATI (high versus low)		0.756 (0.676–0.846)	<0.001	0.870 (0.764–0.992)	0.037
Muscle index (high versus low)		1.042 (0.932–1.165)	0.470
Age group (≥59.5 versus <59.5 years)		1.186 (1.061–1.327)	0.003	0.972 (0.848–1.113)	0.679
Sex (male versus female)		1.579 (1.408–1.770)	<0.001	1.186 (1.010–1.393)	0.037
ECOG performance status (2–4 versus 0–1)		1.257 (1.113–1.420)	<0.001	1.305 (1.153–1.478)	<0.001
Multiple metastases (yes versus no)		1.414 (1.223–1.635)	<0.001	1.350 (1.165–1.565)	<0.001
Site of primary cancer (lung versus other sites)		0.816 (0.727–0.916)	0.001	0.813 (0.716–0.922)	0.001
EQD2Gy (≥32.5 versus <32.5)		0.651 (0.582–0.729)	<0.001	0.802 (0.695–0.925)	0.002
Systemic therapy (yes versus no)		0.584 (0.519–0.658)	<0.001	0.621 (0.546–0.706)	<0.001
Comorbidities (yes versus no)		1.120 (1.000–1.253)	0.049	1.065 (0.948–1.198)	0.288
Education level (high school versus none/primary school)		0.864 (0.772–0.966)	0.010	0.869 (0.763–0.989)	0.033
Cigarette smoking (yes versus no)		1.432 (1.279–1.603)	<0.001	1.092 (0.934–1.276)	0.272
Betel quid chewing (yes versus no)		1.331 (1.139–1.555)	<0.001	0.964 (0.804–1.155)	0.689
Alcohol drinking (yes versus no)		1.373 (1.209–1.560)	<0.001	1.148 (0.989–1.332)	0.069
Days of metastasis treatment (≥13 versus ≤12)		0.704 (0.629–0.787)	<0.001	0.864 (0.750–0.996)	0.044
Onset of metastasis (>1 year versus ≤1 year)		0.800 (0.708–0.904)	<0.001	0.913 (0.801–1.041)	0.175
Place of residence (urban versus rural)		0.985 (0.881–1.102)	0.795
Site of metastasis			0.216
	Bone	1.340 (0.957–1.877)	0.089
	Brain	0.974 (0.821–1.156)	0.765
Employment status			0.556
(low versus high)		1.084 (0.932–1.260)	0.294
(none versus high)		1.034 (0.895–1.195)	0.652
Metastases treatment period (≥2010 versus ≤2009)		0.990 (0.886–1.107)	0.866
Body mass index (>25 versus ≤25 kg/m2)		0.755 (0.664–0.857)	<0.001

Abbreviations: HR, hazard ratio; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; EQD2 Gy, equivalent doses in 2-Gy fractions; SATI, subcutaneous adipose tissue index; VATI, visceral adipose tissue index. An L3 subcutaneous adipose tissue index ≥11.63 cm2 m-2 in males and ≥25.21 cm2 m-2 in females was considered as high. An L3 visceral adipose tissue index ≥10.46 cm2 m-2 in males and ≥8.96 cm2 m-2 in females was considered as high.

Prognostic significance of SATI and VATI

We subsequently examined the prognostic impact of SATI and VATI by classifying patients into high versus low categories. Kaplan-Meier analysis revealed no differences in OS between the high SATI/high VATI group (median survival: 9.37 months) and high SATI/low VATI group (median survival: 9.43 months; P = 0.303; Table 3). The lowest OS (3.97 months) was observed in the low SATI/low VATI group (Fig 1; Table 3).

Table 3

Multivariate Cox regression analysis of overall survival in patients stratified according to subcutaneous adiposity and visceral adiposity.

Subgroup	No. of patients	Median survival time (95% CI)	HR	P value
High SATI/high VATI	455	9.370 (8.116–10.624)		<0.001a
High SATI/low VATI	185	9.436 (7.129–11.742)	1.097 (0.920–1.307)	0.303
Low SATI/high VATI	185	4.603 (3.657–5.548)	1.882 (1.580–2.242)	<0.001a
Low SATI/low VATI	455	3.978 (3.362–4.594)	1.854 (1.622–2.121)	<0.001a

Abbreviations: CI, confidence interval; HR, hazard ratio; SATI, subcutaneous adipose tissue index; VATI, visceral adipose tissue index.

aChi-square test

bANOVA test.

Fig 1

Kaplan-Meier estimates of overall survival in patients with bone metastases stratified according to subcutaneous adiposity (high versus low) and visceral adiposity (high versus low).

Prognostic stratification according to sex and body composition

Thereafter, both sex and SATI values were taken into account to construct four different groups. We specifically selected SATI owing to its higher prognostic value in multivariate analysis. A total of four groups were identified (male/high SATI; female/high SATI; male/low SATI; female/low SATI), with the most favorable survival figures being evident in the female/high SATI group (median OS: 11.21 months; 95% CI: 9.434−12.988 months; P<0.001 versus other groups). The less favorable OS survival (median: 3.847 months; 95% CI: 3.391−4.302 months) was observed in the male/low SATI group (Fig 2; Table 4).

Fig 2

Kaplan-Meier estimates of overall survival in patients with bone metastases stratified according to subcutaneous adiposity (high versus low) and sex (female versus male).

Table 4

Multivariate Cox regression analysis of overall survival in patients stratified according to sex and subcutaneous adiposity.

Subgroup	No. of patients	Median survival time (95%CI)	HR	P value
Female with high SATI	388	11.211 (9.434–12.988)		<0.001a
Female with low SATI	152	5.293 (3.084–7.503)	1.604 (1.324–1.942)	<0.001a
Male with high SATI	252	6.773 (5.481–8.064)	1.312 (1.115–1.545)	<0.001a
Male with low SATI	488	3.847 (3.391–4.302)	2.182 (1.899–2.507)	<0.001a

Abbreviations: CI, confidence interval; HR, hazard ratio; SATI, subcutaneous adipose tissue index.

aChi-square test

bANOVA

Discussion

The results of this retrospective analysis of prospectively collected data can be summarized as follows: 1) high SATI and VATI were independently associated with a better OS in a sample of Taiwanese patients with bone metastases, with the former showing a stronger relationship; 2) the most favorable OS was observed in women with high SATI. Although we observed associations–and not prediction or causation–our study adds to the growing literature investigating adiposity in relation to clinical outcomes of patients with malignancies.[13-15]

Currently, the association of indices of adiposity with the disease course of cancer patients remains controversial. Although adiposity seems to be positively correlated with OS in several solid tumors [16, 17], poorer survival figures have been reported for obese patients with cancer–possibly because of an increased production of growth factors and inflammatory mediators from the adipose tissue.[18] In this regard, it should be noted that adipose tissue may serve as a nutrient replacement in patients with cancer, [15, 19] but it can be also involved in tumor spread through adipokine-induced extracellular matrix remodeling.[20]

Pai et al. [21] have previously shown that SATI is strongly related to distant metastasis-free survival, locoregional control, and OS in 881 patients with head and neck cancer. Ebadi et al. [5] also demonstrated that patients with low SATI and high VATI independently predicted mortality in a sample of patients with different solid malignancies. Herein, we show that VATI, and most prominently SATI, were significantly associated with OS in Taiwanese patients with bone metastases. Controversy still exists on the relationship between VATI and clinical outcomes in patients with solid tumors.[10, 22–24] The reasons whereby SATI appears to hold a stronger association with OS over VATI in our study remain to be elucidated. However, it is notable that–differently from visceral fat (which is an active endocrine organ)–subcutaneous fat is more strictly involved in lipid and energy storage and is characterized by a lower inflammatory environment [14, 25, 26].

The study was conducted in a radiation oncology setting. Bone metastases are not only the most common site of distant spread in patients with solid malignancies but they are also the most commonly identified by radiation oncologists. The question as to whether our findings may be applied to patients with metastases to other distant sites (e.g., liver or brain) remains open. We acknowledge several limitations of the present study. First, the study was conducted in an Asian population, and it is well-known that ethnic differences exist in measures of adiposity between Asian and Caucasian populations [27]. Therefore, our findings need to be independently replicated in other geographic areas. Second, we did not segment body fat in the whole CT volume. Nonetheless, there is published evidence suggesting that measures of adiposity obtained at the L3 level through a simplified CT protocol are well-correlated to those taken at other sites [28-31]. Third, all measures of adiposity were taken in the two week preceding the start of RT. Wu et al. [32] have recently demonstrated the prognostic importance of the time at which body adiposity is assessed. However, these data were not available in this study, and we were unable to run this analysis. Finally, this was a retrospective analysis of prospectively collected data which had an exploratory nature. The application of the Bonferroni’s correction in this setting may be too conservative and was avoided. In any case, our results should be considered as preliminary and hypothesis-generating. Because we observed associations, we cannot claim any prognostic effect of adiposity indices in our population. Future longitudinal studies are required to clarify this issue further.

These limitations notwithstanding, we found that high SATI and VATI are associated with a more favorable OS in Taiwanese patients with bone metastases referred for RT. The question as to whether clinical measures aimed at improving adiposity may improve OS in this clinical population deserves further scrutiny.

2 Dec 2019

PONE-D-19-27964

Independent prognostic significance of subcutaneous and visceral adipose tissue in patients with bone metastases

PLOS ONE

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Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: In the present study, the authors retrospectively investigate the association between SATI, VATI and survival in patients with bone metastases. Although the topic is interesting and the manuscript is overall well written, there are several issues as follows:

1. The association between body fat and survival in many cancers is well-known and established. Hence, the study does not add much new to the current knowledge. However, I acknowledge that this is not necessarily relevant for PLoS ONE, so this point may be disregarded by the editor.

2. The study rationale is not quite clear. Why focus on patients with bone metastases? Other metastases also herald poor prognosis (liver, brain ...).

3. The chance was missed to segment the body fat in the whole CT scan volume and thus provide a more accurate estimate.

4. A biostatistician should be consulted for the statistical analysis, which is not well done (the current analysis leads to spuriously low p-values).

5. The term "predictor" should be avoided throughout the manuscript. In a retrospective study, one can only find associations. Predictions can only be made with a prospective trial. This leads me to the next point:

6. The authors grossly overinterpret the results of their study. Although this is unfortunately the norm in many scientific journals where authors need to "sell" their study, per PLoS ONE policy this is not needed. To give the authors an example: "More importantly, our findings may pave the way for aggressive therapeutic interventions in the subset of patients who are expected to have more favorable survival figures" To make such a statement, a prospective randomised clinical trial is needed.

Reviewer #2: 1. Summary of the research and overall impression

The research entitled "Independent prognostic significance of subcutaneous and visceral adipose tissue in patients with bone metastases" is an interesting and pertinent topic in current discussions of the academic literature.

The main research question addressed by the authors is to discuss whether regional adiposity measures such as subcutaneous adipose tissue index (SATI) and visceral adipose tissue index (VATI) can predict overall survival (OS) in cancer patients with bone metastases.

There is a common perception that, compared with normal-weight patients, elevated BMI is also associated with poorer prognosis after cancer diagnosis. However, some studies have challenged this thinking by showing that among cancer patients, high BMI is associated with improved survival compared with normal weight patients. This finding is known as the obesity paradox, well established in the cardio-metabolic literature, but less appreciated in oncology.

However, some observations of the obesity paradox in cancer reflect methodological mechanisms including the crudeness of BMI as an obesity measure, confounding, detection bias, reverse causality, and selection bias. Thus, when we come across studies on this subject, one should pay attention to these questions so as not to incur mistaken associations.

An important issue to note is that BMI is a relatively crude measure of body adiposity and body composition and does not differentiate between lean mass and fat mass. In turn, body composition varies with age, sex, and ethnicity, such that there are currently no specific age-gender-ethnicity indices to define obesity in a standardized manner. Thus, for example, in a cancer population, overweight individuals (defined by BMI) might be younger with high muscle mass (compared with normal weight), explaining their better outcome compared with normal weight.

The paradox might not exist if alternate measures of body composition or adipose tissue were used. Thus, for example, we found no examples of studies in patients with cancer demonstrating the obesity paradox when anthropometric measures other than BMI or body composition indices were used.

We note that in this study the use of these alternative measures of body composition was used. The authors used regional measures of adiposity, such as the subcutaneous adipose tissue index (SATI) and the visceral adipose tissue index (VATI), which reduces the risk of this paradox and strengthens the consistency of the results presented. We consider this a strength of this study.

The manuscript is technically adequate to its purpose. In analyzing the data provided by the authors, we point out that the results support the conclusions. The information contained in table 1 (p.11-15), table 2 (p.17-19), table 3 (p.21), table 4 (p.23), fig 1 (p.20) and fig 2 (p.22), are well described and provide the necessary information to support the conclusions of this study. The information described in the materials and methods section is clearly written and allows for reproducibility of the study. We also emphasize that the sample size was expressive (1280 cases) and thus appropriate.

However, it is important to emphasize that the use of retrospective design used in this study favors the selection bias and does not allow mechanistic conclusions about the associations found by the authors, this being a weakness of this study. However, they contribute to point out some important paths to follow in future research.

The strategies used to perform the statistical analysis are consistent and suitable for the treatment of the collected data. It is noteworthy that the choice of variables included in the univariate analysis of overall survival, such as cigarette smokin, alcohol drinking, multiple metastases, among others, were important to minimize confounding factors.

When searching this manuscript in several academic databases, no duplicity was found. Therefore, it is believed that the reported results were not published anywhere else.

The research meets the standards applicable to the ethics of experimentation and the integrity of research in humans and has been approved by the Institutional Review Broad Research Ethics Committee (approval number IRB201701224B0).

The authors did not use any public repository to provide data from this study. However, all relevant data are within the manuscript and its supporting information files.

After reviewing this manuscript, considering the editorial criteria for publication employed by PLOS ONE, I suggest approval for publication with “Minor Revision”.

2. Discussion of specific areas for improvement

Major issues

No major issues were identified in the manuscript that compromise the results observed by the authors.

Minor issues

Technical clarifications:

On page 25, the authors report as a limitation of this study: "Body composition was assessed in all patients prior to the first RT session and not when bone metastases were diagnosed." However, they do not clearly explain how this may imply the results found. Thus, I suggest to the authors, as a minor review, to further clarify this issue, given that the time when BMI was determined is relevant to the observed patterns of association.

We suggest the authors review the World Cancer Research Fund (WCRF) report on the effect of risk factors on survival among women with breast cancer. This recent report added a very useful classification—namely, determination of BMI either at pre-, peri-, or post-diagnosis (the later typically 12 months after the initial treatment) of câncer. From these, different patterns of associations emerge. In a meta-analysis of 29 studies evaluating the impact of BMI on survival in patients with colorectal cancer, Wu et al. observed that increasing pre-diagnosis BMI prognosticated for a poor survival but that post-treatment overweight was associated with improved survival, i.e., the obesity paradox.

Suggested References to Authors:

WCRF. World Cancer Research Fund International. Continuous Update Project Report: diet, nutrition, physical activity, and breast cancer survivors. 2014. Available at:www.wcrf.org/sites/default/files/Breast-Cancer-Survivors-2014-Report.pdf [Accessed 20th Dec 2014]. 2014.

Wu S, Liu J, Wang X, Li M, Gan Y, Tang Y. Association of obesity and overweight with overall survival in colorectal cancer patients: a meta-analysis of 29 studies. Cancer Causes Control. 2014;25:1489–1502. doi: 10.1007/s10552-014-0450-y.

Reviewer #3: I consider the piece is valuable. However, results must be explained more in detail to be able to trace interpretations offered at discussion. Manuscript should be reviewed for grammatical errors (for example patient demographics, should be more in relation to the concept assessment than the way variables were implemented), specially for critical interpretations of data and analyses. Recommendations for more aggressive therapeutics is not included in the analysis, but is being offered as a conclusion, therefore I recommend to review this issue and explain more about how this is derived from the analysis.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Milena Castro

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20 Dec 2019

AUTHORS’ REPLY TO REVIEWER’S #1 COMMENTS

1. The association between body fat and survival in many cancers is well-known and established. Hence, the study does not add much new to the current knowledge. However, I acknowledge that this is not necessarily relevant for PLoS ONE, so this point may be disregarded by the editor.

REPLY. We thank the Reviewer for the constructive criticism. We concur that the association between adiposity and survival in patients with malignancies has been extensively investigated in the past. However, this study may represent a valid addition to the existing literature for the following reasons: 1) the association of subcutaneous adiposity and visceral adiposity with survival endpoints in patients with cancer remains controversial, 2) we specifically focused on patients with bone metastases who were referred for radiotherapy (see below for further clarifications on study population); 3) the study was conducted in an Asian population (it is well-known that ethnic differences exist in measures of adiposity between Asian and Caucasian populations). We believe that these points should be considered when dealing with the novelty of our work. Please note that the title has been revised to highlight the ethnic origin of the study population.

The study rationale is not quite clear. Why focus on patients with bone metastases? Other metastases also herald poor prognosis (liver, brain ...).

REPLY. We are grateful to the Reviewer for the cogent comment. We specifically focused on bone metastases for the following reasons. First, the study was conducted in a radiation oncology setting. Bone metastases are not only the most common site of distant spread in patients with solid malignancies but they are also the most commonly identified by radiation oncologists. We did focus on bone metastases not only because they portend a poor prognosis, but also in light of their high frequency. Second, patients with bone metastases commonly present with pain and an impaired quality of life, ultimately requiring referral for radiotherapy. We therefore believe that our study population is of special interest for radiation therapists. We nonetheless acknowledged the lack of inclusion of patients with metastases at other sites as a limitation inherent in our study (please see the revised “Discussion” section).

The chance was missed to segment the body fat in the whole CT scan volume and thus provide a more accurate estimate.

REPLY. We concur with the Reviewer that whole-body computed tomography (CT) can actually provide a more accurate and comprehensive estimation of adiposity. However, there is published evidence (see references 1−4 below) suggesting that measures of adiposity obtained at the L3 level through a simplified CT protocol are well-correlated to those taken at other sites. We are aware that this is a potential limitation inherent in our study, which has been acknowledged in the revised “Discussion” section.

A biostatistician should be consulted for the statistical analysis, which is not well done (the current analysis leads to spuriously low p-values).

REPLY. This study was designed as a retrospective analysis of prospectively collected data (a point which has been clarified in revised paper). The statistical approach was in line with the analyses conducted in other published papers from our group (see references 5−8 below). With regard to the low p-values, they may stem from a multiple comparison problem. However, the application of the Bonferroni’s correction may be too conservative in an exploratory analysis. We nonetheless believe that this is a potential caveat inherent in our study, which has been addressed in the revised “Discussion” section.

5. The term "predictor" should be avoided throughout the manuscript. In a retrospective study, one can only find associations. Predictions can only be made with a prospective trial. This leads me to the next point

REPLY. We thank the Reviewer for the pertinent observation. In the revised version of the paper, we made appropriate revisions to highlight that we observed associations, not prediction or causation. We also acknowledged the retrospective design as a major study limitation in the “Discussion” section.

6. The authors grossly overinterpret the results of their study. Although this is unfortunately the norm in many scientific journals where authors need to "sell" their study, per PLoS ONE policy this is not needed. To give the authors an example: "More importantly, our findings may pave the way for aggressive therapeutic interventions in the subset of patients who are expected to have more favorable survival figures" To make such a statement, a prospective randomised clinical trial is needed.

REPLY. The Reviewer is entirely right and we apologize for the excessive emphasis put on the significance of our findings. In the revised version of the paper, several statements were toned down, the main limitations were highlighted, and the conclusions were drawn more prudently. We have highlighted these points as a relevant future research topic in the revised “Discussion” section.

References

1. Shen W, Punyanitya M, Wang Z, Gallagher D, St-Onge MP, Albu J, Heymsfield SB, Heshka S. Visceral adipose tissue: relations between single-slice areas and total volume. Am J Clin Nutr 2004;80:271–278.

2. Noumura Y, Kamishima T, Sutherland K, Nishimura H. Visceral adipose tissue area measurement at a single level: can it represent visceral adipose tissue volume? Br J Radiol 2017;90:20170253.

3. Schweitzer L, Geisler C, Pourhassan M, Braun W, Gluer CC, Bosy- Westphal A, Muller MJ. What is the best reference site for a single MRI slice to assess whole-body skeletal muscle and adipose tissue volumes in healthy adults? Am J Clin Nutr 2015;102:58–65.

4. Demerath EW, Shen W, Lee M, Choh AC, Czerwinski SA, Siervogel RM, Towne B. Approximation of total visceral adipose tissue with a single magnetic resonance image. Am J Clin Nutr 2007;85:362-368.

5. Tsang NM, Pai PC, Chuang CC, Chuang WC, Tseng CK, Chang KP, Yen TC, Lin JD, Chang JT. Overweight and obesity predict better overall survival rates in cancer patients with distant metastases. Cancer Med 2016;5(4):665–675.

6. Pai PC, Chuang CC, Chuang WC, Tsang NM, Tseng CK, Chen KH, et al. Pretreatment subcutaneous adipose tissue predicts the outcomes of patients with head and neck cancer receiving definitive radiation and chemoradiation in Taiwan. Cancer Med. 2018;7:1630–1641.

7. Pai PC, Chuang CC, Tseng CK, Tsang NM, Chang KP, Yen TC, et al. Impact of pretreatment body mass index on patients with head-and-neck cancer treated with radiation. Int J Radiat Oncol Biol Phys. 2012;83:e93-e100.

8. Tsang NM, Chuang CC, Tseng CK, Hao SP, Kuo TT, Lin CY et al. Presence of the latent membrane protein 1 gene in nasopharyngeal swabs from patients with mucosal recurrent nasopharyngeal carcinoma. Cancer 2003;98:2385–2392.

AUTHORS’ REPLY TO REVIEWER’S #2 COMMENTS

On page 25, the authors report as a limitation of this study: "Body composition was assessed in all patients prior to the first RT session and not when bone metastases were diagnosed." However, they do not clearly explain how this may imply the results found. Thus, I suggest to the authors, as a minor review, to further clarify this issue, given that the time when BMI was determined is relevant to the observed patterns of association.

We suggest the authors review the World Cancer Research Fund (WCRF) report on the effect of risk factors on survival among women with breast cancer. This recent report added a very useful classification—namely, determination of BMI either at pre-, peri-, or post-diagnosis (the later typically 12 months after the initial treatment) of câncer. From these, different patterns of associations emerge. In a meta-analysis of 29 studies evaluating the impact of BMI on survival in patients with colorectal cancer, Wu et al. observed that increasing pre-diagnosis BMI prognosticated for a poor survival but that post-treatment overweight was associated with improved survival, i.e., the obesity paradox.

Suggested References to Authors:

WCRF. World Cancer Research Fund International. Continuous Update Project Report: diet, nutrition, physical activity, and breast cancer survivors. 2014. Available at:www.wcrf.org/sites/default/files/Breast-Cancer-Survivors-2014-Report.pdf [Accessed 20th Dec 2014]. 2014.

Wu S, Liu J, Wang X, Li M, Gan Y, Tang Y. Association of obesity and overweight with overall survival in colorectal cancer patients: a meta-analysis of 29 studies. Cancer Causes Control. 2014;25:1489–1502. doi: 10.1007/s10552-014-0450-y.

REPLY. We thank the Reviewer for the constructive observations. In the revised version of the paper, we clarified that all measures of adiposity were taken in the two week preceding the start of RT. With regard to the World Cancer Research Fund (WCRF) report and the paper by Wu et al., we realize the prognostic importance of the time at which body adiposity is assessed. However, these data were not available in this study, and we were therefore unable to run this analysis. We have highlighted this point as a relevant future research topic in the revised “Discussion” section.

We had mentioned in the Discussion line 256: “Fourth, all measures of adiposity were taken in the two week preceding the start of RT. Wu et al. (32) have recently demonstrated the prognostic importance of the time at which body adiposity is assessed. However, the data of post-diagnosis of cancer (12 months after initial treatment) were not available in this study, and we were unable to run this analysis. ”

AUTHORS’ REPLY TO REVIEWER’S #3 COMMENTS

I consider the piece is valuable. However, results must be explained more in detail to be able to trace interpretations offered at discussion. Manuscript should be reviewed for grammatical errors (for example patient demographics, should be more in relation to the concept assessment than the way variables were implemented), specially for critical interpretations of data and analyses. Recommendations for more aggressive therapeutics is not included in the analysis, but is being offered as a conclusion, therefore I recommend to review this issue and explain more about how this is derived from the analysis.

REPLY. We thank the Reviewer for the constructive criticisms. In order to address the concern, the following changes were implemented: 1) the paper has been revised for style and presentation; 2) the nature of the analysis was clarified (retrospective analysis of prospectively collected data) and any reference to prediction or causation were removed; 3) we removed the emphasis on therapeutic recommendations because we realize that they are unwarranted based on our current data.

Submitted filename: Response to Reviewers.doc

Click here for additional data file.

14 Jan 2020

Association of subcutaneous and visceral adipose tissue with overall survival in Taiwanese patients with bone metastases – results from a retrospective analysis of consecutively collected data

PONE-D-19-27964R1

Dear Dr. Tsang,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: We identified from line 247 of the revised “Discussion” section that adjustments have been made to the text to justify the prognostic significance of the time when body adiposity is assessed and highlighted by the authors as a relevant topic for future research. However, the authors adequately responded to the observations and suggestions for improvement we proposed. We agree to approve the revised manuscript for publication.

Reviewer #3: (No Response)

**********

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Reviewer #2: No

Reviewer #3: Yes: Milena Castro

16 Jan 2020

PONE-D-19-27964R1

Association of subcutaneous and visceral adipose tissue with overall survival in Taiwanese patients with bone metastases – results from a retrospective analysis of consecutively collected data

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