An analysis of lactate dehydrogenase (LDH) levels in advanced stage IV melanoma of the skin: prognostic capabilities and demographic variability

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Desai, Sree Chinta, Christopher Yeh, Vraj P. Shah, Radhika Shah, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1915668/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Despite its limitations, in part due to decreased specificity in advanced disease, serum lactate dehydrogenase (LDH) is one of few serum factors used in cancer staging. Objectives This study quantifies the predictive capabilities of LDH in stage IV melanoma of the skin and explores the validity of suggested demographic discrepancies which may exist in its use. Methods The 1975–2017 Surveillance Epidemiology and End Results (SEER) database was queried for stage IV cutaneous melanoma cases. Demographic characteristics were compared between LDH groups using chi-square and t-tests. Subsequent Cox multivariable regression was performed to assess survival differences. Results 334 cases of stage IV cutaneous melanoma (average age: 63.0 years) with measured serum LDH levels were identified. Of these patients, 150 (44.9%) had normal LDH, 112 (33.5%) had LDH 10x ULN. Lower incomes were associated with higher LDH; individuals with incomes 10x ULN also had the lowest proportion of White patients (p = 0.04). On Cox multivariable survival analysis, increasing LDH levels showed increased risk of death (LDH < 1.5x ULN: HR = 2.05, p = 0.01; LDH 1.5-10x ULN: HR = 1.46, p 10x ULN: HR = 5.91, p < 0.001). Conclusion This study reaffirms the utility of LDH as a significant predictor of mortality with incremental severity, suggesting possible use for mortality projections. We note that Black patients and those with lower incomes may be more likely to have an elevated LDH. Older age groups and presence of ulceration among patients with stage IV melanoma were also associated with a greater risk of mortality. LDH melanoma SEER serum lactate dehydrogenase stage IV melanoma Introduction Malignant melanoma is a common cancer with a low five-year survival rate of 16.7% for stage IV tumors. [1,2] Treatment of melanoma has great economic implications, costing each stage IV melanoma patient between $ 34,103 to $ 152,244 annually, and the US melanoma patient population 65 years and older $ 390 million cumulatively every year. [3,4] Thankfully, the majority of the 106,110 new cutaneous cases of skin melanoma were detected prior reaching stage IV. [3,4] Previous studies have suggested metastasis and serum lactate dehydrogenase (sLDH) levels as possible predictors of survival, with sLDH remaining as one of the few serum factors used for cancer staging today. [5,6] However, the utility of sLDH as a prognostic factor, specifically for metastasis, has yet to be performed on a national scale. [7] Significant limitations with current use of sLDH as a biomarker have been noted, such as LDH not being an actively secreted enzyme and so it is only released by active cell death, occurring more frequently in malignant neoplasms, and the number of false-positives with hemolysis, hepatocellular and muscular diseases, and other malignancies. [8,9] While the specificity of sLDH level as a biomarker for detecting presence of melanoma increases with stage, up to 92% for stage IV, sensitivity of sLDH decreases as stage progresses with stage IV having 79% sensitivity, leading to a propensity for false negatives. [10] Although the use of sLDH level have been used in the American Joint Committee on Cancer (AJCC) staging system for melanoma for over a decade, demographic characterization of sLDH and delineating which patients benefit most from its predictive capabilities remain unexplored on a national level. [11] Furthermore, LDH’s ability to predict various responses to treatment, such as to anti-PD1/PD-L1 therapy, remains an area of interest. [12] The largest disparity in survival rates between Black and White patients in absolute terms, as estimated by the American Cancer Society in its 2021 statistical data, was found to be present in melanoma (25%). [13] Furthermore, with shorter survival times due to melanoma in Blacks and other non-White races, it is possible that predictive tools often used in staging for melanoma, like sLDH, lack similar effectiveness in predicting mortality for people of color compared to White patients. This study aims to use the statistical power of a large national database to analyze the effects of sLDH levels on perioperative outcomes, as well as the associations of sLDH with demographic characteristics in patients with stage IV melanoma. Materials And Methods A retrospective analysis of the 1975–2017 Surveillance Epidemiology and End Results (SEER) database was queried for stage IV skin melanoma cases. Data was collected in compliance with the ethics and terms in the SEER Research Data Use Agreement. We obtained several clinical characteristics for each patient including age, sLDH, primary site of tumor, and disease-specific survival. We also collected other demographic information like insurance status and income level. Once stage IV skin melanoma cases were identified, eligibility requirements for inclusion into the study included presence of measured sLDH within the SEER database. Patients with an unknown sLDH were excluded. SLDH was stratified into four groups based upon pre-existing SEER categories: normal, sLDH < 1.5x upper limit of normal (ULN), sLDH 1.5-10x ULN, and sLDH 10x normal. These levels included only pre-treatment sLDH levels. Breslow thickness was divided at the limit of 4 mm, to allow for comparisons with previously published studies. [14,15] Univariable and multivariable analyses were performed using Microsoft Excel (Microsoft, Seattle, WA) and SAS Software (SAS Studio Release 3.8, Cary, North Carolina). Demographic characteristics of the included patients were compared using a combination of chi-squared and ANOVA tests between sLDH groups. Finally, Cox multivariable survival analysis was performed on investigated variables using disease-specific survival. Statistical tests used a two-sided alpha-value of 0.05. Results Of 194,491 patients with melanoma of the skin in the SEER database, 1,523 patients with stage IV skin melanoma were selected. Of these patients, 334 patients were found to have stage IV melanoma with complete sLDH information and were included in the final study. Of these patients, 150 (44.9%) had normal sLDH values, 112 (33.5%) had sLDH values 10x ULN. The mean age of included patients was 63.0 (STDDEV: 13.8) years old. Of included patients, 237 (71.0%) were male and 97 (29.0%) were female. A majority of the patients were White, with 323 (96.7%) identified as White. Upon comparison of demographic variables between sLDH groups, (Table 1 ) there were no differences in age (p = 0.997) or gender (p = 0.5643) between the four sLDH groups. Significant differences were observed in race, with the highest proportion of Black patients (13.3%) falling in the sLDH > 10x ULN group (p = 0.0359, Table 1 ). Significant differences were also observed in terms of income; patients in the sLDH > 10x ULN group had the greatest proportion of individuals with incomes $65,000 (69.3%) (p = 0.0031, Table 1 ). Table 1 Demographic characteristics of 334 included patients. Variable Normal (n = 150) (44.9%) 10x ULN (n = 15) (4.5%) p-value Age (continuous) 63.0 (14.3) 63.1 (13.2) 62.9 (13.6) 62.9 (15.2) 0.9970 Age (categorical) 0.6282 < 50 25 (16.7) 16 (14.3) 8 (14.0) 3 (20.0) 50–59 32 (21.3) 28 (25.0) 10 (17.5) 3 (20.0) 60–69 37 (24.7) 29 (25.9) 16 (28.1) 4 (26.7) 70–79 35 (23.3) 24 (21.4) 19 (33.3) 1 (6.7) 80+ 21 (14.0) 15 (13.4) 4 (7.0) 4 (26.7) Sex 0.5643 Female 44 (29.3) 28 (25.0) 20 (35.1) 5 (33.3) Male 106 (70.7) 84 (75.0) 37 (64.9) 10 (66.7) Race 0.0359 White 146 (97.3) 108 (96.4) 56 (98.3) 13 (86.7) Black 0 (0) 1 (0.9) 1 (1.8) 2 (13.3) Other 4 (2.7) 2 (1.8) 0 (0) 0 (0) Unknown 0 (0) 1 (0.9) 0 (0) 0 (0) Primary Site 0.9165 Skin of the eyelid, ear, or face NOS 9 (6.0) 2 (1.8) 3 (5.3) 0 (0) Skin of the scalp and neck 17 (11.3) 9 (8.0) 5 (8.8) 0 (0) Skin of the trunk 21 (14.0) 19 (17.0) 8 (14.0) 3 (20.0) Skin of the upper limb and shoulder 9 (6.0) 5 (4.5) 4 (7.0) 1 (6.67) Skin of the lower limb and hip 9 (6.0) 10 (8.9) 5 (8.8) 1 (6.67) Skin, NOS 85 (56.7) 67 (59.8) 32 (56.1) 10 (66.7) Ulceration 0.2577 No Ulceration 51 (34.0) 33 (29.5) 12 (21.1) 3 (20.0) Ulceration 21 (14.0) 23 (20.5) 16 (28.1) 3 (20.0) Unknown 78 (52.0) 56 (50.0) 29 (50.9) 9 (60.0) Number of Tumors 0.5200 One 93 (62.0) 79 (70.5) 40 (70,2) 11 (73.3) Two 40 (26.7) 26 (23.2) 14 (24.6) 2 (13.3) Three or more 17 (11.3) 7 (6.3) 3 (5.3) 2 (13.3) Breslow Thickness (cont.) (mm) 19.6 (31.2) 22.4 (35.2) 21.0 (34.5) 11.9 (30.6) 0.7939 Breslow Thickness (mm) 0.7542 4 or less 103 (68.7) 80 (71.4) 42 (73.7) 12 (80.0) Over 4 47 (31.3) 32 (28.6) 15 (26.3) 3 (20.0) Income 0.0031 <$50.000 9 (6.0) 10 (8.9) 2 (3.5) 5 (33.3) $50,000-$65,000 37 (24.7) 26 (23.2) 21 (36.8) 2 (13.3) $65,000+ 104 (69.3) 76 (67.9) 34 (59.7) 8 (53.3) Histology 0.6580 Melanoma, NOS 112 (74.6) 88 (78.6) 45 (79.0) 11 (73.3) Nodular 19 (12.7) 14 (12.5) 9 (15.8) 2 (13.3) Acral 9 (6.0) 3 (2.7) 0 (0) 0 (0) Other 10 (6.7) 7 (6.2) 3 (5.3) 2 (13.3) Of specified primary tumor sites, the most common site among all sLDH groups was skin of the trunk. There were no significant differences in primary tumor location between the sLDH groups (p = 0.9165, Table 1 ). Additionally, no differences were observed in tumor ulceration (p = 0.2577), number of tumors (p = 0.5200), and Breslow thickness of tumors (p = 0.7939) between the sLDH groups. On Cox multivariable survival analysis (Table 2 ), age was a significant predictor of mortality, with worsening mortality outcomes observed for ages 50–59 (Hazard Ratio (HR):1.5, p = 0.0430), 70–79 (HR:1.9, p = 0.0007), and over 80 (HR:2.0, p = 0.0012) years old when compared to those less than 50 years old. Positive ulceration was a significant predictor of mortality (HR:1.7, p = 0.0112), whereas unknown ulceration status was associated with better mortality outcomes (HR:1.0, p = 0.0286) when compared to those with no ulceration (Table 2 ). When compared to those with normal sLDH levels, elevated sLDH < 1.5x ULN (HR:2.1, p 10x ULN (HR:5.9, p 10x ULN group. Table 2 Cox multivariable survival analysis of variables. Variable Estimate Standard Error Hazard Ratio 95% Confidence Interval p-value Age < 50 REF 50–59 0.39 0.19 1.47 0.981 2.111 0.0430 60–69 0.25 0.18 1.28 0.891 1.827 0.1798 70–79 0.65 0.19 1.92 1.297 2.759 0.0007 80+ 0.71 0.22 2.04 1.324 3.135 0.0012 Sex Female REF Male -0.08662 0.13007 0.917 0.716 1.191 0.5054 Race White REF Black -0.26 0.58 0.78 0.230 2.213 0.6600 Other 0.69 0.43 1.99 0.878 4.667 0.1100 Unknown -0.59 1.02 0.56 0.075 4.104 0.5700 Income <$50.000 REF $50,000-$65,000 0.06 0.25 1.06 0.650 1.734 0.8123 $65,000+ -0.3 0.24 0.76 0.478 1.221 0.2598 Primary Site Skin, NOS REF Skin of eyelid, ear, or face NOS 0.02 0.34 1.02 0.507 1.885 0.9499 Skin of lower limb and hip -0.58 0.28 0.59 0.336 1.019 0.0581 Skin of scalp and neck -0.21 0.27 0.81 0.483 1.464 0.4366 Skin of trunk -0.11 0.23 0.9 0.593 1.533 0.6341 Skin of upper limb and shoulder 0.25 0.27 1.28 0.743 2.099 0.3539 Ulceration No Ulceration REF Ulceration 0.49 0.24 1.63 1.082 2.444 0.0194 Unknown -0.05 0.27 0.96 0.682 1.338 0.7907 Number of Tumors One REF Two 0.04 0.14 1.04 0.796 1.368 0.7600 Three or more -0.16 0.22 0.85 0.573 1.366 0.4600 Breslow Thickness (mm) 4 or less REF Over 4 -0.27 0.22 0.76 0.496 1.169 0.2133 LDH Normal REF < 1.5x ULN 0.72 0.17 2.05 1.496 2.862 10x ULN 1.78 0.34 5.91 3.381 12.331 < 0.0001 Discussion In this study, we elucidate the relationship between sLDH levels and various demographic factors as well as examine the contributions of demographic, disease etiology, and biomarker variables to mortality risk in stage IV melanoma patients. Between 1975 and 2017, 334 patients were found with stage IV melanoma and known sLDH levels in the SEER database. Using SEER-generated categories of normal sLDH, normal to 1.5 times upper limit of normal (ULN), 1.5 to 10 times ULN, and greater than 10 times ULN, we examined the association between sLDH and perioperative variables, including demographic characteristics and mortality. We found that 44.9% of these 334 patients had normal sLDH levels, 33.5% had normal to 1.5 times ULN, 17.1% had 1.5 to 10 times ULN, and 4.5% had greater than 10 times ULN, with 78.1% of the original stage IV melanoma population having unknown sLDH values. The distribution of patients in each sLDH level is similar to the distribution expected based on previous studies. Although previous studies have explored the effects of sLDH on postoperative outcomes in patients with melanoma, few studies have investigated the relationship between sLDH and postoperative outcomes in stage IV melanoma patients specifically using a large national database. [16,17] Although previous studies on racial discrepancies in sLDH levels are limited, our findings indicate an association between race and sLDH levels, with Black patients having a higher proportion of members with sLDH greater than 10 times ULN (p = 0.04, Table 1 ) compared to White patients. While the exact cause for this difference is unknown, one possibility is that healthcare disparities lead to Black patients being diagnosed at a later stage and less likely to receive chemotherapy, radiation therapy, and surgery in a timely manner, resulting in greater tumor growth and sLDH levels. [18,19] In addition, Black patients have a higher percentage of acrolentigious melanomas (including subungual melanomas), associated with a much worse prognosis than typical cutaneous melanomas on sun-exposed skin. [20] Subungual melanoma represents approximately 1–3% of all cutaneous melanomas in the White population, yet up to 75% of Black melanomas. [21] Therefore, delay in diagnosis and treatment for Black patients may also be due to the rarity of melanoma in Blacks overall and the anatomic sites of its appearance especially on the palms and soles, compared to more commonly sun-exposed regions in White patients. [22,23] Following various forms of melanoma treatment and controlling for differences in treatment quality and socioeconomic status, Black patients were still found to have poorer survival, indicating that non-treatment-related factors like tumor biology and cancer biomarkers may be possible explanations for racial disparities in survival. [24] For example, sLDH was found to be positively associated with fibulin-1 and ROS in Blacks only; this increase in extracellular matrix remodeling and oxidative stress may have implications for melanoma prognosis. [25] Our Cox survival analysis found no difference in mortality risk of any race subpopulation compared to that of White patients when controlling for sex, income, primary tumor site, ulceration status, number of tumors, and sLDH level. This finding is contrary to the conclusions from other studies that Black and Hispanic patients have significantly higher mortality rates compared to white patients. [26,27] The insignificant racial difference in mortality risk may be due to the limited sample size of Black patients with stage IV melanoma documented in the SEER database. Furthermore, as a number of variables were controlled for in our model compared to those of other studies solely examining the effect of race on mortality, it is likely that some of the mortality differences by race can be explained by these other variables. The prognosis of stage IV melanoma is already poor with limited options for treatment compared to earlier stages of melanoma, so there is less possibility for race-based variations in mortality risk. [28,29] Ward-Peterson et al.’s (2016) study [30] analyzed SEER data over a 30-year period and found that while Black melanoma patients had a higher cause-specific and all-cause risk of mortality compared to white patients, this difference became insignificant after adjusting for site and stage of diagnosis. These findings emphasize the need for early detection and treatment of melanoma, which can be accomplished by improving physician efforts to clinically and histologically diagnose melanoma in black patients, as well as educate the black population on melanoma. [31] We also noted an association between income and sLDH levels, with patients in the lowest income class of less than $ 50,000 having a higher proportion of sLDH levels greater than 10 times ULN, a relationship that has not been explored in the literature. However, our Cox survival analysis found that income level, like race, did not impact risk of mortality when controlling for confounders, contrary to income being inversely related to risk of mortality in other studies. [32] The difference between our findings and those in other studies could be due to our use of the levels of income stratified by the SEER database that are more granular than those used in these other studies. Patients of lower socioeconomic status are more likely to rely on Medicaid or lack insurance altogether, while patients of higher socioeconomic status are more likely to have commercial insurance. It has been well-documented that melanoma patients with commercial insurance have better survival outcomes compared to those who are covered by Medicaid or lack insurance. [33,34] Higher sLDH levels in these lower-income patients provides a possible explanation for their poorer survival outcomes but since SEER only provides insurance status data for 2007 onwards, we cannot correlate insurance status with survival using our sample. Our finding that patients with sLDH levels normal to 1.5 times ULN, 1.5 to 10 times ULN, and greater than 10 times ULN have worse survival compared to patients with normal sLDH levels appears to be consistent with the Warburg Effect as well as clinical findings on the use of sLDH as a prognostic factor in melanoma. [35–37] We also found that ulceration is associated with an increased risk of mortality as in accordance with other studies. [38,39] Ulceration has been found to be a predictor of mortality independent of age, sex, tumor thickness, site, and mitoses per millimeter, while sLDH has been found to be a predictor of mortality independent of gender, visceral organ involvement, platelet count, age, performance status, tumor thickness, and time to stage IV diagnosis. [40–44] However, ulceration and sLDH have not been shown in the literature to be predictors of mortality independent of each other. Presence of ulceration indicates a more aggressive tumor, and the prognostic ability of sLDH independent of ulceration demonstrates that sLDH has predictive value in melanoma cases beyond reflecting the aggressiveness of the tumor. All older age groups of patients had a greater risk of mortality compared to the group of patients less than 50 years old except for the group of patients between 60 and 69 years, who did not have a significantly different risk of mortality. There was no significant difference in sLDH levels between age groups, affirming that age and sLDH levels are independent predictors of mortality in melanoma patients. [45,46] The findings of other studies are mixed on the effect of age on mortality. Lideikaitė et al. (2017) [47] found that patients aged 65 years and older have a lower ten-year survival rate than that of younger cohorts, but there is no significant difference in melanoma-specific mortality among these cohorts. Chao et al. (2004) [48] and Lasithiotakis et al. (2008) [49] found that as age increases, the incidence of poor prognostic factors like Breslow thickness, incidence of ulceration, and male gender increases. Some studies have found that age does not correlate with risk of mortality in melanoma patients at all, while others contend that age correlates positively with risk of mortality in localized and regional disease but not in distant disease. [50,51] Given the ambivalent conclusions regarding the association between age and mortality, it is important that future studies using large databases calculate stage-specific and melanoma-specific mortality, and control for localized or regional disease versus distant disease. There are limitations to consider in this study. First, since our study is based on the SEER database, variations in ICD-9 and − 10 coding and incomplete information upon entry of patient values by health practitioners caused many of the sLDH values and ulceration statuses of patients to be recorded as unknown. Therefore, despite the use of a very large sample with Stage IV melanoma, the vast majority of these patients had to be excluded due to missing information for these important prognostic factors. Another factor contributing to missing values for variables that require patient follow-up is that patient movement out of the 20 geographic areas covered by SEER could disproportionately affect certain patient subpopulations more than others. Many melanoma cases are reported to cancer registries like SEER only years after diagnosis, which may impact mortality statistics because as melanoma treatment and care improves in more recent years, mortality decreases. [52] Although SEER is a national database, the incidence of melanoma in minority populations is sufficiently low such that the sample size of Black patients makes it difficult to draw conclusions with absolute certainty. Furthermore, given the diversity in a condition like melanoma, and various demographics affected more by certain subtypes (i.e. acral lentiginous melanoma in Black patients), direct comparison between demographic groups may not be a perfect comparison. Taking these limitations into consideration may at least partly explain the differences between the presented conclusions in this study and the findings of other studies related to the relationship between race and mortality and between sLDH and mortality. [53,54] Conclusions This review of 334 stage IV melanoma patients revealed that elevated levels of sLDH, from as low as normal to 1.5 times ULN, are significantly associated with increased risk of mortality. Furthermore, Black patients and patients with lower incomes were found to have greater sLDH levels, so despite the insignificant difference in risk of mortality by race and income, further research is needed to assess the contribution of elevated sLDH levels in these populations to risk of mortality. Older age groups and presence of ulceration among patients with stage IV melanoma were also associated with a greater risk of mortality. Declarations Competing Interests: None Acknowledgements: None. Compliance with Ethical Standards: Funding: None. Potential conflicts of interest: AD, SC, CY, VS, RS, BP, RS all declare they have no conflicts of interest to report. Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. References Atkinson V. 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Am J Prev Med . 2008;35(1):7-13. doi:10.1016/j.amepre.2008.03.026 Halpern MT, Ward EM, Pavluck AL, Schrag NM, Bian J, Chen AY. Association of insurance status and ethnicity with cancer stage at diagnosis for 12 cancer sites: a retrospective analysis. Lancet Oncol . 2008;9(3):222-231. doi:10.1016/S1470-2045(08)70032-9 Petrelli F, Ardito R, Merelli B, et al. Prognostic and predictive role of elevated lactate dehydrogenase in patients with melanoma treated with immunotherapy and BRAF inhibitors: a systematic review and meta-analysis. Melanoma Res . 2019;29(1):1-12. doi:10.1097/CMR.0000000000000520 Deckers EA, Kruijff S, Brouwers AH, et al. The association between active tumor volume, total lesion glycolysis and levels of S-100B and LDH in stage IV melanoma patients. Eur J Surg Oncol J Eur Soc Surg Oncol Br Assoc Surg Oncol . 2020;46(11):2147-2153. doi:10.1016/j.ejso.2020.07.011 Zhang J, Yao YH, Li BG, Yang Q, Zhang PY, Wang HT. Prognostic value of pretreatment serum lactate dehydrogenase level in patients with solid tumors: a systematic review and meta-analysis. Sci Rep . 2015;5:9800. doi:10.1038/srep09800 Risk of Melanoma Recurrence After Diagnosis of a High-Risk Primary Tumor | Dermatology | JAMA Dermatology | JAMA Network. Accessed July 13, 2021. https://jamanetwork.com/journals/jamadermatology/fullarticle/2731995 Balch CM, Wilkerson JA, Murad TM, Soong SJ, Ingalls AL, Maddox WA. The prognostic significance of ulceration of cutaneous melanoma. Cancer . 1980;45(12):3012-3017. doi:10.1002/1097-0142(19800615)45:123.0.co;2-o in ’t Hout FEM, Haydu LE, Murali R, Bonenkamp JJ, Thompson JF, Scolyer RA. Prognostic Importance of the Extent of Ulceration in Patients With Clinically Localized Cutaneous Melanoma. Ann Surg . 2012;255(6):1165-1170. doi:10.1097/SLA.0b013e31824c4b0b Bønnelykke-Behrndtz ML, Schmidt H, Christensen IJ, et al. Prognostic Stratification of Ulcerated Melanoma: Not Only the Extent Matters. Am J Clin Pathol . 2014;142(6):845-856. doi:10.1309/AJCPW56PHGLFTKZC Sirott MN, Bajorin DF, Wong GY, et al. Prognostic factors in patients with metastatic malignant melanoma. A multivariate analysis. Cancer . 1993;72(10):3091-3098. doi:10.1002/1097-0142(19931115)72:103.0.co;2-v Nieder C, Marienhagen K, Dalhaug A, Norum J. Towards Improved Prognostic Scores Predicting Survival in Patients with Brain Metastases: A Pilot Study of Serum Lactate Dehydrogenase Levels. Sci World J . 2012;2012:e609323. doi:10.1100/2012/609323 Weide B, Elsässer M, Büttner P, et al. Serum markers lactate dehydrogenase and S100B predict independently disease outcome in melanoma patients with distant metastasis. Br J Cancer . 2012;107(3):422-428. doi:10.1038/bjc.2012.306 Balch CM, Soong S jaw, Gershenwald JE, et al. Age as a Prognostic Factor in Patients with Localized Melanoma and Regional Metastases. Ann Surg Oncol . 2013;20(12):3961-3968. doi:10.1245/s10434-013-3100-9 Shen W, Sakamoto N, Yang L. Melanoma-specific mortality and competing mortality in patients with non-metastatic malignant melanoma: a population-based analysis. BMC Cancer . 2016;16(1):413. doi:10.1186/s12885-016-2438-3 Lideikaitė A, Mozūraitienė J, Letautienė S. Analysis of prognostic factors for melanoma patients. Acta Medica Litu . 2017;24(1):25-34. doi:10.6001/actamedica.v24i1.3460 Chao C, Martin RCG, Ross MI, et al. Correlation Between Prognostic Factors and Increasing Age in Melanoma. Ann Surg Oncol . 2004;11(3):259-264. doi:10.1245/ASO.2004.04.015 Lasithiotakis K, Leiter U, Meier F, et al. Age and gender are significant independent predictors of survival in primary cutaneous melanoma. Cancer . 2008;112(8):1795-1804. doi:10.1002/cncr.23359 Weiss SA, Han J, Darvishian F, et al. Impact of aging on host immune response and survival in melanoma: an analysis of 3 patient cohorts. J Transl Med . 2016;14(1):299. doi:10.1186/s12967-016-1026-2 Enninga EAL, Moser JC, Weaver AL, et al. Survival of cutaneous melanoma based on sex, age, and stage in the United States, 1992–2011. Cancer Med . 2017;6(10):2203-2212. doi:10.1002/cam4.1152 Cockburn M, Swetter SM, Peng D, Keegan THM, Deapen D, Clarke CA. Melanoma underreporting: why does it happen, how big is the problem, and how do we fix it? J Am Acad Dermatol . 2008;59(6):1081-1085. doi:10.1016/j.jaad.2008.08.007 Mahendraraj K, Sidhu K, Lau CSM, McRoy GJ, Chamberlain RS, Smith FO. Malignant Melanoma in African–Americans. Medicine (Baltimore) . 2017;96(15):e6258. doi:10.1097/MD.0000000000006258 Brady J, Kashlan R, Ruterbusch J, Farshchian M, Moossavi M. Racial Disparities in Patients with Melanoma: A Multivariate Survival Analysis. Clin Cosmet Investig Dermatol . 2021;14:547-550. doi:10.2147/CCID.S311694 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 11 Oct, 2022 Reviewers agreed at journal 11 Oct, 2022 Reviews received at journal 11 Oct, 2022 Reviewers agreed at journal 11 Oct, 2022 Reviewers invited by journal 30 Aug, 2022 Submission checks completed at journal 01 Aug, 2022 Editor assigned by journal 01 Aug, 2022 First submitted to journal 31 Jul, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1915668","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":125519365,"identity":"60fd3058-0a44-4d28-bcb8-d0974c9d14c0","order_by":0,"name":"Amar D. Desai","email":"","orcid":"","institution":"Rutgers New Jersey Medical School","correspondingAuthor":false,"prefix":"","firstName":"Amar","middleName":"D.","lastName":"Desai","suffix":""},{"id":125519366,"identity":"27b80eef-3f87-4341-b036-edc3c531d02b","order_by":1,"name":"Sree Chinta","email":"","orcid":"","institution":"Rutgers New Jersey Medical School","correspondingAuthor":false,"prefix":"","firstName":"Sree","middleName":"","lastName":"Chinta","suffix":""},{"id":125519367,"identity":"89855930-6aa3-49b3-8a9c-e0441867e06c","order_by":2,"name":"Christopher Yeh","email":"","orcid":"","institution":"Rutgers New Jersey Medical School","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Yeh","suffix":""},{"id":125519368,"identity":"691aa109-5757-49f3-98c8-160df89091ee","order_by":3,"name":"Vraj P. Shah","email":"","orcid":"","institution":"Rutgers New Jersey Medical School","correspondingAuthor":false,"prefix":"","firstName":"Vraj","middleName":"P.","lastName":"Shah","suffix":""},{"id":125519369,"identity":"05dcae2e-a143-4bdf-aa6f-d9063e819329","order_by":4,"name":"Radhika Shah","email":"","orcid":"","institution":"Rutgers Robert Wood Johnson Medical School","correspondingAuthor":false,"prefix":"","firstName":"Radhika","middleName":"","lastName":"Shah","suffix":""},{"id":125519370,"identity":"11bb3399-0e0d-4145-a818-c20651f0720a","order_by":5,"name":"Boris Paskhover","email":"","orcid":"","institution":"Rutgers New Jersey Medical School","correspondingAuthor":false,"prefix":"","firstName":"Boris","middleName":"","lastName":"Paskhover","suffix":""},{"id":125519371,"identity":"7611e190-dcc1-4608-b751-da5b8b7229c9","order_by":6,"name":"Robert A. Schwartz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYJACZih1AEhIyBCvhYeBLQGkhYcULTwGEJoQMG8//vBzYZtdvj3/mc+vbtRY8DCwHz66AZ8WmTM5xtIz25ItexjObrPOOQZ0GE9a2g18WiQYctiYebcxG/Aw9m4zzmEDapHgMcOvhf/5M6CWegMeZp5nxjn/iNEikWAG1HLYgIeNh/lxbhtRWt4YS/P+O27Ac4bNjDm3TwKolZBf+NMffuY5U23A3n/48eecb3Vy/OyHj+HVggzYJMAkscpBgPkDKapHwSgYBaNg5AAA+M88Uu6xc9cAAAAASUVORK5CYII=","orcid":"","institution":"Rutgers New Jersey Medical School","correspondingAuthor":true,"prefix":"","firstName":"Robert","middleName":"A.","lastName":"Schwartz","suffix":""}],"badges":[],"createdAt":"2022-08-01 02:29:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1915668/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1915668/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":24741878,"identity":"a719cf79-d8cf-4696-9f22-527cdaefec47","added_by":"auto","created_at":"2022-08-03 18:20:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":380545,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1915668/v1/67c2d298-83da-4175-b4de-948011976169.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An analysis of lactate dehydrogenase (LDH) levels in advanced stage IV melanoma of the skin: prognostic capabilities and demographic variability","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalignant melanoma is a common cancer with a low five-year survival rate of 16.7% for stage IV tumors.\u003csup\u003e[1,2]\u003c/sup\u003e Treatment of melanoma has great economic implications, costing each stage IV melanoma patient between \u003cspan\u003e$\u003c/span\u003e34,103 to \u003cspan\u003e$\u003c/span\u003e152,244 annually, and the US melanoma patient population 65 years and older \u003cspan\u003e$\u003c/span\u003e390\u0026nbsp;million cumulatively every year. \u003csup\u003e[3,4]\u003c/sup\u003e Thankfully, the majority of the 106,110 new cutaneous cases of skin melanoma were detected prior reaching stage IV. \u003csup\u003e[3,4]\u003c/sup\u003e \u003c/p\u003e \u003cp\u003ePrevious studies have suggested metastasis and serum lactate dehydrogenase (sLDH) levels as possible predictors of survival, with sLDH remaining as one of the few serum factors used for cancer staging today. \u003csup\u003e[5,6]\u003c/sup\u003e However, the utility of sLDH as a prognostic factor, specifically for metastasis, has yet to be performed on a national scale. \u003csup\u003e[7]\u003c/sup\u003e Significant limitations with current use of sLDH as a biomarker have been noted, such as LDH not being an actively secreted enzyme and so it is only released by active cell death, occurring more frequently in malignant neoplasms, and the number of false-positives with hemolysis, hepatocellular and muscular diseases, and other malignancies. \u003csup\u003e[8,9]\u003c/sup\u003e While the specificity of sLDH level as a biomarker for detecting presence of melanoma increases with stage, up to 92% for stage IV, sensitivity of sLDH decreases as stage progresses with stage IV having 79% sensitivity, leading to a propensity for false negatives. \u003csup\u003e[10]\u003c/sup\u003e Although the use of sLDH level have been used in the American Joint Committee on Cancer (AJCC) staging system for melanoma for over a decade, demographic characterization of sLDH and delineating which patients benefit most from its predictive capabilities remain unexplored on a national level. \u003csup\u003e[11]\u003c/sup\u003e Furthermore, LDH\u0026rsquo;s ability to predict various responses to treatment, such as to anti-PD1/PD-L1 therapy, remains an area of interest. \u003csup\u003e[12]\u003c/sup\u003e The largest disparity in survival rates between Black and White patients in absolute terms, as estimated by the American Cancer Society in its 2021 statistical data, was found to be present in melanoma (25%).\u003csup\u003e[13]\u003c/sup\u003e Furthermore, with shorter survival times due to melanoma in Blacks and other non-White races, it is possible that predictive tools often used in staging for melanoma, like sLDH, lack similar effectiveness in predicting mortality for people of color compared to White patients. This study aims to use the statistical power of a large national database to analyze the effects of sLDH levels on perioperative outcomes, as well as the associations of sLDH with demographic characteristics in patients with stage IV melanoma.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eA retrospective analysis of the 1975\u0026ndash;2017 Surveillance Epidemiology and End Results (SEER) database was queried for stage IV skin melanoma cases. Data was collected in compliance with the ethics and terms in the SEER Research Data Use Agreement. We obtained several clinical characteristics for each patient including age, sLDH, primary site of tumor, and disease-specific survival. We also collected other demographic information like insurance status and income level.\u003c/p\u003e \u003cp\u003eOnce stage IV skin melanoma cases were identified, eligibility requirements for inclusion into the study included presence of measured sLDH within the SEER database. Patients with an unknown sLDH were excluded. SLDH was stratified into four groups based upon pre-existing SEER categories: normal, sLDH\u0026thinsp;\u0026lt;\u0026thinsp;1.5x upper limit of normal (ULN), sLDH 1.5-10x ULN, and sLDH 10x normal. These levels included only pre-treatment sLDH levels. Breslow thickness was divided at the limit of 4 mm, to allow for comparisons with previously published studies. \u003csup\u003e[14,15]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eUnivariable and multivariable analyses were performed using Microsoft Excel (Microsoft, Seattle, WA) and SAS Software (SAS Studio Release 3.8, Cary, North Carolina). Demographic characteristics of the included patients were compared using a combination of chi-squared and ANOVA tests between sLDH groups. Finally, Cox multivariable survival analysis was performed on investigated variables using disease-specific survival. Statistical tests used a two-sided alpha-value of 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOf 194,491 patients with melanoma of the skin in the SEER database, 1,523 patients with stage IV skin melanoma were selected. Of these patients, 334 patients were found to have stage IV melanoma with complete sLDH information and were included in the final study. Of these patients, 150 (44.9%) had normal sLDH values, 112 (33.5%) had sLDH values\u0026thinsp;\u0026lt;\u0026thinsp;1.5x ULN, 57 (17.1%) had sLDH values 1.5-10x ULN, and 15 (4.5%) had sLDH values\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN.\u003c/p\u003e\n\u003cp\u003eThe mean age of included patients was 63.0 (STDDEV: 13.8) years old. Of included patients, 237 (71.0%) were male and 97 (29.0%) were female. A majority of the patients were White, with 323 (96.7%) identified as White.\u003c/p\u003e\n\u003cp\u003eUpon comparison of demographic variables between sLDH groups, (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) there were no differences in age (p\u0026thinsp;=\u0026thinsp;0.997) or gender (p\u0026thinsp;=\u0026thinsp;0.5643) between the four sLDH groups. Significant differences were observed in race, with the highest proportion of Black patients (13.3%) falling in the sLDH\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN group (p\u0026thinsp;=\u0026thinsp;0.0359, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Significant differences were also observed in terms of income; patients in the sLDH\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN group had the greatest proportion of individuals with incomes \u0026lt;$50,000 (33.3%) whereas patients in the normal sLDH group had the highest proportion of individuals with incomes \u0026gt;$65,000 (69.3%) (p\u0026thinsp;=\u0026thinsp;0.0031, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic characteristics of 334 included patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNormal (n\u0026thinsp;=\u0026thinsp;150) (44.9%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1.5x ULN (n\u0026thinsp;=\u0026thinsp;112) (33.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1.5-10x ULN (n\u0026thinsp;=\u0026thinsp;57) (17.1%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;10x ULN (n\u0026thinsp;=\u0026thinsp;15) (4.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (continuous)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.0 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.1 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.9 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.9 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9970\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (categorical)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026ndash;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026ndash;79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106 (70.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0359\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146 (97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108 (96.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (98.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of the eyelid, ear, or face NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of the scalp and neck\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of the trunk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of the upper limb and shoulder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of the lower limb and hip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin, NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (59.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (56.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUlceration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Ulceration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33 (29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUlceration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Tumors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93 (62.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79 (70.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (70,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThree or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreslow Thickness (cont.) (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.6 (31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.4 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.0 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7939\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreslow Thickness (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 or less\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103 (68.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80 (71.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOver 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;$50.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$50,000-$65,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$65,000+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e104 (69.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76 (67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (59.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6580\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMelanoma, NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112 (74.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88 (78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (79.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNodular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAcral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eOf specified primary tumor sites, the most common site among all sLDH groups was skin of the trunk. There were no significant differences in primary tumor location between the sLDH groups (p\u0026thinsp;=\u0026thinsp;0.9165, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, no differences were observed in tumor ulceration (p\u0026thinsp;=\u0026thinsp;0.2577), number of tumors (p\u0026thinsp;=\u0026thinsp;0.5200), and Breslow thickness of tumors (p\u0026thinsp;=\u0026thinsp;0.7939) between the sLDH groups.\u003c/p\u003e\n\u003cp\u003eOn Cox multivariable survival analysis (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), age was a significant predictor of mortality, with worsening mortality outcomes observed for ages 50\u0026ndash;59 (Hazard Ratio (HR):1.5, p\u0026thinsp;=\u0026thinsp;0.0430), 70\u0026ndash;79 (HR:1.9, p\u0026thinsp;=\u0026thinsp;0.0007), and over 80 (HR:2.0, p\u0026thinsp;=\u0026thinsp;0.0012) years old when compared to those less than 50 years old. Positive ulceration was a significant predictor of mortality (HR:1.7, p\u0026thinsp;=\u0026thinsp;0.0112), whereas unknown ulceration status was associated with better mortality outcomes (HR:1.0, p\u0026thinsp;=\u0026thinsp;0.0286) when compared to those with no ulceration (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). When compared to those with normal sLDH levels, elevated sLDH\u0026thinsp;\u0026lt;\u0026thinsp;1.5x ULN (HR:2.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 1.5-10x ULN (HR:1.5, p\u0026thinsp;=\u0026thinsp;0.0043), and \u0026gt;\u0026thinsp;10x ULN (HR:5.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) were all significant predictors of mortality, with the greatest hazard ratio found in the sLDH\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN group.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCox multivariable survival analysis of variables.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard Error\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% Confidence Interval\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u0026ndash;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0430\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1798\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u0026ndash;79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.08662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;$50.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$50,000-$65,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.8123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$65,000+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2598\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin, NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of eyelid, ear, or face NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of lower limb and hip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0581\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of scalp and neck\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of trunk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin of upper limb and shoulder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.3539\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUlceration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Ulceration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUlceration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0194\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Tumors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThree or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreslow Thickness (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 or less\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOver 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.2133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eREF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1.5x ULN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5-10x ULN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;10x ULN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we elucidate the relationship between sLDH levels and various demographic factors as well as examine the contributions of demographic, disease etiology, and biomarker variables to mortality risk in stage IV melanoma patients. Between 1975 and 2017, 334 patients were found with stage IV melanoma and known sLDH levels in the SEER database. Using SEER-generated categories of normal sLDH, normal to 1.5 times upper limit of normal (ULN), 1.5 to 10 times ULN, and greater than 10 times ULN, we examined the association between sLDH and perioperative variables, including demographic characteristics and mortality. We found that 44.9% of these 334 patients had normal sLDH levels, 33.5% had normal to 1.5 times ULN, 17.1% had 1.5 to 10 times ULN, and 4.5% had greater than 10 times ULN, with 78.1% of the original stage IV melanoma population having unknown sLDH values. The distribution of patients in each sLDH level is similar to the distribution expected based on previous studies. Although previous studies have explored the effects of sLDH on postoperative outcomes in patients with melanoma, few studies have investigated the relationship between sLDH and postoperative outcomes in stage IV melanoma patients specifically using a large national database. \u003csup\u003e[16,17]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAlthough previous studies on racial discrepancies in sLDH levels are limited, our findings indicate an association between race and sLDH levels, with Black patients having a higher proportion of members with sLDH greater than 10 times ULN (p\u0026thinsp;=\u0026thinsp;0.04, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) compared to White patients. While the exact cause for this difference is unknown, one possibility is that healthcare disparities lead to Black patients being diagnosed at a later stage and less likely to receive chemotherapy, radiation therapy, and surgery in a timely manner, resulting in greater tumor growth and sLDH levels. \u003csup\u003e[18,19]\u003c/sup\u003e In addition, Black patients have a higher percentage of acrolentigious melanomas (including subungual melanomas), associated with a much worse prognosis than typical cutaneous melanomas on sun-exposed skin. \u003csup\u003e[20]\u003c/sup\u003e Subungual melanoma represents approximately 1\u0026ndash;3% of all cutaneous melanomas in the White population, yet up to 75% of Black melanomas. \u003csup\u003e[21]\u003c/sup\u003e Therefore, delay in diagnosis and treatment for Black patients may also be due to the rarity of melanoma in Blacks overall and the anatomic sites of its appearance especially on the palms and soles, compared to more commonly sun-exposed regions in White patients. \u003csup\u003e[22,23]\u003c/sup\u003e Following various forms of melanoma treatment and controlling for differences in treatment quality and socioeconomic status, Black patients were still found to have poorer survival, indicating that non-treatment-related factors like tumor biology and cancer biomarkers may be possible explanations for racial disparities in survival. \u003csup\u003e[24]\u003c/sup\u003e For example, sLDH was found to be positively associated with fibulin-1 and ROS in Blacks only; this increase in extracellular matrix remodeling and oxidative stress may have implications for melanoma prognosis. \u003csup\u003e[25]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur Cox survival analysis found no difference in mortality risk of any race subpopulation compared to that of White patients when controlling for sex, income, primary tumor site, ulceration status, number of tumors, and sLDH level. This finding is contrary to the conclusions from other studies that Black and Hispanic patients have significantly higher mortality rates compared to white patients. \u003csup\u003e[26,27]\u003c/sup\u003e The insignificant racial difference in mortality risk may be due to the limited sample size of Black patients with stage IV melanoma documented in the SEER database. Furthermore, as a number of variables were controlled for in our model compared to those of other studies solely examining the effect of race on mortality, it is likely that some of the mortality differences by race can be explained by these other variables. The prognosis of stage IV melanoma is already poor with limited options for treatment compared to earlier stages of melanoma, so there is less possibility for race-based variations in mortality risk. \u003csup\u003e[28,29]\u003c/sup\u003e Ward-Peterson et al.\u0026rsquo;s (2016) study\u003csup\u003e[30]\u003c/sup\u003e analyzed SEER data over a 30-year period and found that while Black melanoma patients had a higher cause-specific and all-cause risk of mortality compared to white patients, this difference became insignificant after adjusting for site and stage of diagnosis. These findings emphasize the need for early detection and treatment of melanoma, which can be accomplished by improving physician efforts to clinically and histologically diagnose melanoma in black patients, as well as educate the black population on melanoma. \u003csup\u003e[31]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWe also noted an association between income and sLDH levels, with patients in the lowest income class of less than \u003cspan\u003e$\u003c/span\u003e50,000 having a higher proportion of sLDH levels greater than 10 times ULN, a relationship that has not been explored in the literature. However, our Cox survival analysis found that income level, like race, did not impact risk of mortality when controlling for confounders, contrary to income being inversely related to risk of mortality in other studies. \u003csup\u003e[32]\u003c/sup\u003e The difference between our findings and those in other studies could be due to our use of the levels of income stratified by the SEER database that are more granular than those used in these other studies. Patients of lower socioeconomic status are more likely to rely on Medicaid or lack insurance altogether, while patients of higher socioeconomic status are more likely to have commercial insurance. It has been well-documented that melanoma patients with commercial insurance have better survival outcomes compared to those who are covered by Medicaid or lack insurance. \u003csup\u003e[33,34]\u003c/sup\u003e Higher sLDH levels in these lower-income patients provides a possible explanation for their poorer survival outcomes but since SEER only provides insurance status data for 2007 onwards, we cannot correlate insurance status with survival using our sample.\u003c/p\u003e \u003cp\u003eOur finding that patients with sLDH levels normal to 1.5 times ULN, 1.5 to 10 times ULN, and greater than 10 times ULN have worse survival compared to patients with normal sLDH levels appears to be consistent with the Warburg Effect as well as clinical findings on the use of sLDH as a prognostic factor in melanoma. \u003csup\u003e[35\u0026ndash;37]\u003c/sup\u003e We also found that ulceration is associated with an increased risk of mortality as in accordance with other studies. \u003csup\u003e[38,39]\u003c/sup\u003e Ulceration has been found to be a predictor of mortality independent of age, sex, tumor thickness, site, and mitoses per millimeter, while sLDH has been found to be a predictor of mortality independent of gender, visceral organ involvement, platelet count, age, performance status, tumor thickness, and time to stage IV diagnosis. \u003csup\u003e[40\u0026ndash;44]\u003c/sup\u003e However, ulceration and sLDH have not been shown in the literature to be predictors of mortality independent of each other. Presence of ulceration indicates a more aggressive tumor, and the prognostic ability of sLDH independent of ulceration demonstrates that sLDH has predictive value in melanoma cases beyond reflecting the aggressiveness of the tumor.\u003c/p\u003e \u003cp\u003eAll older age groups of patients had a greater risk of mortality compared to the group of patients less than 50 years old except for the group of patients between 60 and 69 years, who did not have a significantly different risk of mortality. There was no significant difference in sLDH levels between age groups, affirming that age and sLDH levels are independent predictors of mortality in melanoma patients. \u003csup\u003e[45,46]\u003c/sup\u003e The findings of other studies are mixed on the effect of age on mortality. Lideikaitė et al. (2017) \u003csup\u003e[47]\u003c/sup\u003e found that patients aged 65 years and older have a lower ten-year survival rate than that of younger cohorts, but there is no significant difference in melanoma-specific mortality among these cohorts. Chao et al. (2004) \u003csup\u003e[48]\u003c/sup\u003e and Lasithiotakis et al. (2008) \u003csup\u003e[49]\u003c/sup\u003e found that as age increases, the incidence of poor prognostic factors like Breslow thickness, incidence of ulceration, and male gender increases. Some studies have found that age does not correlate with risk of mortality in melanoma patients at all, while others contend that age correlates positively with risk of mortality in localized and regional disease but not in distant disease. \u003csup\u003e[50,51]\u003c/sup\u003e Given the ambivalent conclusions regarding the association between age and mortality, it is important that future studies using large databases calculate stage-specific and melanoma-specific mortality, and control for localized or regional disease versus distant disease.\u003c/p\u003e \u003cp\u003eThere are limitations to consider in this study. First, since our study is based on the SEER database, variations in ICD-9 and \u0026minus;\u0026thinsp;10 coding and incomplete information upon entry of patient values by health practitioners caused many of the sLDH values and ulceration statuses of patients to be recorded as unknown. Therefore, despite the use of a very large sample with Stage IV melanoma, the vast majority of these patients had to be excluded due to missing information for these important prognostic factors. Another factor contributing to missing values for variables that require patient follow-up is that patient movement out of the 20 geographic areas covered by SEER could disproportionately affect certain patient subpopulations more than others. Many melanoma cases are reported to cancer registries like SEER only years after diagnosis, which may impact mortality statistics because as melanoma treatment and care improves in more recent years, mortality decreases. \u003csup\u003e[52]\u003c/sup\u003e Although SEER is a national database, the incidence of melanoma in minority populations is sufficiently low such that the sample size of Black patients makes it difficult to draw conclusions with absolute certainty. Furthermore, given the diversity in a condition like melanoma, and various demographics affected more by certain subtypes (i.e. acral lentiginous melanoma in Black patients), direct comparison between demographic groups may not be a perfect comparison. Taking these limitations into consideration may at least partly explain the differences between the presented conclusions in this study and the findings of other studies related to the relationship between race and mortality and between sLDH and mortality. \u003csup\u003e[53,54]\u003c/sup\u003e\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis review of 334 stage IV melanoma patients revealed that elevated levels of sLDH, from as low as normal to 1.5 times ULN, are significantly associated with increased risk of mortality. Furthermore, Black patients and patients with lower incomes were found to have greater sLDH levels, so despite the insignificant difference in risk of mortality by race and income, further research is needed to assess the contribution of elevated sLDH levels in these populations to risk of mortality. Older age groups and presence of ulceration among patients with stage IV melanoma were also associated with a greater risk of mortality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements: \u003c/strong\u003eNone.\u003c/p\u003e\n\u003cp\u003eCompliance with Ethical Standards:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eFunding: None.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePotential conflicts of interest: AD, SC, CY, VS, RS, BP, RS all declare they have no conflicts of interest to report.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eEthical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAtkinson V. 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Age as a Prognostic Factor in Patients with Localized Melanoma and Regional Metastases. \u003cem\u003eAnn Surg Oncol\u003c/em\u003e. 2013;20(12):3961-3968. doi:10.1245/s10434-013-3100-9\u003c/li\u003e\n\u003cli\u003eShen W, Sakamoto N, Yang L. Melanoma-specific mortality and competing mortality in patients with non-metastatic malignant melanoma: a population-based analysis. \u003cem\u003eBMC Cancer\u003c/em\u003e. 2016;16(1):413. doi:10.1186/s12885-016-2438-3\u003c/li\u003e\n\u003cli\u003eLideikaitė A, Mozūraitienė J, Letautienė S. Analysis of prognostic factors for melanoma patients. \u003cem\u003eActa Medica Litu\u003c/em\u003e. 2017;24(1):25-34. doi:10.6001/actamedica.v24i1.3460\u003c/li\u003e\n\u003cli\u003eChao C, Martin RCG, Ross MI, et al. Correlation Between Prognostic Factors and Increasing Age in Melanoma. \u003cem\u003eAnn Surg Oncol\u003c/em\u003e. 2004;11(3):259-264. doi:10.1245/ASO.2004.04.015\u003c/li\u003e\n\u003cli\u003eLasithiotakis K, Leiter U, Meier F, et al. Age and gender are significant independent predictors of survival in primary cutaneous melanoma. \u003cem\u003eCancer\u003c/em\u003e. 2008;112(8):1795-1804. doi:10.1002/cncr.23359\u003c/li\u003e\n\u003cli\u003eWeiss SA, Han J, Darvishian F, et al. Impact of aging on host immune response and survival in melanoma: an analysis of 3 patient cohorts. \u003cem\u003eJ Transl Med\u003c/em\u003e. 2016;14(1):299. doi:10.1186/s12967-016-1026-2\u003c/li\u003e\n\u003cli\u003eEnninga EAL, Moser JC, Weaver AL, et al. Survival of cutaneous melanoma based on sex, age, and stage in the United States, 1992\u0026ndash;2011. \u003cem\u003eCancer Med\u003c/em\u003e. 2017;6(10):2203-2212. doi:10.1002/cam4.1152\u003c/li\u003e\n\u003cli\u003eCockburn M, Swetter SM, Peng D, Keegan THM, Deapen D, Clarke CA. Melanoma underreporting: why does it happen, how big is the problem, and how do we fix it? \u003cem\u003eJ Am Acad Dermatol\u003c/em\u003e. 2008;59(6):1081-1085. doi:10.1016/j.jaad.2008.08.007\u003c/li\u003e\n\u003cli\u003eMahendraraj K, Sidhu K, Lau CSM, McRoy GJ, Chamberlain RS, Smith FO. Malignant Melanoma in African\u0026ndash;Americans. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e. 2017;96(15):e6258. doi:10.1097/MD.0000000000006258\u003c/li\u003e\n\u003cli\u003eBrady J, Kashlan R, Ruterbusch J, Farshchian M, Moossavi M. Racial Disparities in Patients with Melanoma: A Multivariate Survival Analysis. \u003cem\u003eClin Cosmet Investig Dermatol\u003c/em\u003e. 2021;14:547-550. doi:10.2147/CCID.S311694\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"LDH, melanoma, SEER, serum lactate dehydrogenase, stage IV melanoma","lastPublishedDoi":"10.21203/rs.3.rs-1915668/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1915668/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDespite its limitations, in part due to decreased specificity in advanced disease, serum lactate dehydrogenase (LDH) is one of few serum factors used in cancer staging.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eThis study quantifies the predictive capabilities of LDH in stage IV melanoma of the skin and explores the validity of suggested demographic discrepancies which may exist in its use.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe 1975\u0026ndash;2017 Surveillance Epidemiology and End Results (SEER) database was queried for stage IV cutaneous melanoma cases. Demographic characteristics were compared between LDH groups using chi-square and t-tests. Subsequent Cox multivariable regression was performed to assess survival differences.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e 334 cases of stage IV cutaneous melanoma (average age: 63.0 years) with measured serum LDH levels were identified. Of these patients, 150 (44.9%) had normal LDH, 112 (33.5%) had LDH\u0026thinsp;\u0026lt;\u0026thinsp;1.5x upper limit of normal (ULN), 57 (17.1%) had LDH 1.5-10x ULN, and 15 (4.5%) had LDH\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN. Lower incomes were associated with higher LDH; individuals with incomes \u0026lt;\u003cspan\u003e$\u003c/span\u003e50,000 had the greatest proportion of LDH 10x ULN (19.2%; p\u0026thinsp;=\u0026thinsp;0.0031). LDH\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN also had the lowest proportion of White patients (p\u0026thinsp;=\u0026thinsp;0.04). On Cox multivariable survival analysis, increasing LDH levels showed increased risk of death (LDH\u0026thinsp;\u0026lt;\u0026thinsp;1.5x ULN: HR\u0026thinsp;=\u0026thinsp;2.05, p\u0026thinsp;=\u0026thinsp;0.01; LDH 1.5-10x ULN: HR\u0026thinsp;=\u0026thinsp;1.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; LDH\u0026thinsp;\u0026gt;\u0026thinsp;10x ULN: HR\u0026thinsp;=\u0026thinsp;5.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study reaffirms the utility of LDH as a significant predictor of mortality with incremental severity, suggesting possible use for mortality projections. We note that Black patients and those with lower incomes may be more likely to have an elevated LDH. Older age groups and presence of ulceration among patients with stage IV melanoma were also associated with a greater risk of mortality.\u003c/p\u003e","manuscriptTitle":"An analysis of lactate dehydrogenase (LDH) levels in advanced stage IV melanoma of the skin: prognostic capabilities and demographic variability","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-03 18:20:05","doi":"10.21203/rs.3.rs-1915668/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2022-10-11T18:52:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2570d6d2-add8-4e68-bf66-0311b0bc0adf","date":"2022-10-11T18:52:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-10-11T18:51:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c4aa9135-8f21-419f-bef8-fd497e6ccf2a","date":"2022-10-11T18:50:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-08-30T16:21:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-08-01T12:09:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-08-01T12:09:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Dermatological Research","date":"2022-08-01T02:27:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-dermatological-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Archives of Dermatological Research](https://www.springer.com/journal/403)","snPcode":"403","submissionUrl":"https://submission.nature.com/new-submission/403/3","title":"Archives of Dermatological Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8c1df12d-9046-4858-b3b2-dabd3b0ce581","owner":[],"postedDate":"August 3rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-10-13T19:59:20+00:00","versionOfRecord":[],"versionCreatedAt":"2022-08-03 18:20:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1915668","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1915668","identity":"rs-1915668","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}