{
  "abstract": "Background The PREVENT equations offer a contemporary tool for estimating long-term cardiovascular (CV) risk in the general population. 1 2 However, their prognostic significance in cancer survivors remains unclear. This study evaluates the association of baseline CV risk, calculated by PREVENT equations, with all-cause and CV mortality in cancer survivors.Methods Using 10 years of data from the National Health and Nutrition Examination Survey (NHANES) (2009–2018), we analysed a cohort representing over 18 million U.S. cancer survivors to evaluate the association between baseline CV risk, as defined by the PREVENT equations, and long-term all-cause and CV mortality. A Cox proportional hazards model was used to evaluate the relationship with all-cause mortality, while competing risk analysis was applied for CV mortality using the Fine and Gray semiparametric proportional hazards model, accounting for the competing risk of non-CV mortality. Models were adjusted for family income, education level, and cancer site. All statistical analyses were based on weighted records.Results A total of 18,722,334 weighted records (2,792 unweighted) were analysed, recording 4,875,627 all-cause deaths (26%) and 1,025,053 CV deaths (5.5%) over a 118-month median follow-up. When compared to low-risk individuals, those at high CV risk had a nearly sixteenfold higher risk of all-cause mortality (aHR: 15.60, 95% CI: 8.45–28.82, p < 0.001) and a fourteenfold higher risk of CV mortality (sHR: 14.01, 95% CI: 3.37–58.26, p < 0.001) during up to a decade of follow-up. Each 5% increase in baseline CV risk was associated with higher risks of all-cause mortality (36%) and CV mortality (50%) (aHR: 1.36 [95% CI: 1.30–1.42], sHR: 1.50 [95% CI: 1.35–1.66], p < 0.001 for both).Conclusion This study highlights the usefulness of the PREVENT score across diverse cancer survivor populations in predicting all-cause and CV mortality outcomes regardless of cancer site.References Khan SS, Coresh J, Pencina MJ, Ndumele CE, Rangaswami J, Chow SL, et al. Novel prediction equations for absolute risk assessment of total cardiovascular disease incorporating cardiovascular-kidney-metabolic health: a scientific statement from the american heart association. Circulation [Internet]. 2023 Dec 12 [cited 2025 Mar 6];148(24):1982–2004. Available from: https://pubmed.ncbi.nlm.nih.gov/37947094/.Scheuermann B, Brown A, Colburn T, Hakeem H, Chen ,, Chow H, et al. External validation of the American heart association PREVENT cardiovascular disease risk equations key points + invited commentary + supplemental content. JAMA Netw Open. 2024;7(10):2438311.Abstract 7-006 Table 1Survey-weighted baseline characteristics of study participants by baseline CV risk according to PREVENT equations Characteristic OverallN = 18,722,3341 LowN = 5,834,043(31.16%)1 BorderlineN = 1,862,598 (9.94%)1 IntermediateN = 5,812,854 (31%)1 HighN = 5,212,840 (27.84%)1 p-value 2 All-cause mortality 4,875,627 (26%) 304,564 (5.2%) 388,561 (21%) 1,194,340 (21%) 2,988,163 (57%) <0.001 CV mortality 1,025,053 (5.5%) 45,456 (0.8%) 0 (0%) 58,904 (1.0%) 920,694 (18%) <0.001 Follow up time 119 (109, 125) 122 (118, 128) 116 (109, 122) 121 (112, 125) 103 (59, 123) <0.001 Age (years) 64 (53, 75) 48 (36, 54) 58 (54, 60) 67 (63, 72) 80 (76, 80) <0.001 Gender <0.001 Men 8,086,481 (43%) 1,071,249 (18%) 1,205,270 (65%) 3,077,311 (53%) 2,732,650 (52%) Women 10,635,853 (57%) 4,762,793 (82%) 657,328 (35%) 2,735,543 (47%) 2,480,189 (48%) Race/Ethnicity 0.068 Mexican American 436,470 (2.3%) 224,546 (3.8%) 24,825 (1.3%) 108,005 (1.9%) 79,094 (1.5%) Other Hispanic 338,855 (1.8%) 211,976 (3.6%) 55,813 (3.0%) 35,925 (0.6%) 35,140 (0.7%) Non-Hispanic White 16,622,281 (89%) 4,791,720 (82%) 1,661,596 (89%) 5,360,890 (92%) 4,808,074 (92%) Non-Hispanic Black 896,477 (4.8%) 323,306 (5.5%) 120,364 (6.5%) 162,276 (2.8%) 290,531 (5.6%) Other Race 428,251 (2.3%) 282,494 (4.8%) 0 (0%) 145,757 (2.5%) 0 (0%) Ratio of family income to poverty <0.001 <1.31 2,487,894 (13%) 856,764 (15%) 68,459 (3.7%) 713,277 (12%) 849,393 (16%) 1.31–1.85 1,560,477 (8.3%) 413,903 (7.1%) 21,743 (1.2%) 563,064 (9.7%) 561,766 (11%) 1.86–3.5 4,361,467 (23%) 765,010 (13%) 349,358 (19%) 1,258,024 (22%) 1,989,075 (38%) >3.5 10,312,496 (55%) 3,798,365 (65%) 1,423,037 (76%) 3,278,488 (56%) 1,812,605 (35%) Education level 0.040 Less than High School 3,086,543 (16%) 817,698 (14%) 148,397 (8.0%) 1,002,886 (17%) 1,117,563 (21%) High school or equivalent 3,776,805 (20%) 766,258 (13%) 317,884 (17%) 1,280,589 (22%) 1,412,073 (27%) More than High school 11,858,985 (63%) 4,250,087 (73%) 1,396,317 (75%) 3,529,379 (61%) 2,683,203 (51%) Systolic blood pressure (mm Hg) 124 (112, 136) 114 (106, 124) 120 (110, 134) 126 (114, 138) 136 (124, 150) <0.001 Body Mass Index (kg/m**2) 28 (24, 33) 27 (24, 33) 28 (25, 33) 29 (24, 34) 28 (24, 31) 0.6 Total Cholesterol (mg/dL) 191 (165, 219) 192 (166, 221) 191 (158, 228) 202 (177, 227) 180 (155, 208) 0.001 Direct HDL-Cholesterol (mg/dL) 51 (42, 65) 56 (45, 66) 48 (40, 60) 50 (42, 68) 51 (40, 62) 0.2 GFR (ml/min) 89 (66, 109) 106 (91, 140) 98 (81, 123) 84 (68, 105) 60 (45, 74) <0.001 Glycohemoglobin (%) 5.60 (5.30, 6.00) 5.30 (5.20, 5.60) 5.50 (5.30, 5.70) 5.80 (5.50, 6.10) 5.80 (5.50, 6.30) <0.001 Active smoking 2,415,228 (13%) 1,137,310 (19%) 371,732 (20%) 624,323 (11%) 281,863 (5.4%) 0.006 Hypertension medication 7,834,640 (42%) 829,405 (14%) 461,261 (25%) 2,669,833 (46%) 3,874,141 (74%) <0.001 Hyperlipidemia medication 5,381,873 (29%) 429,655 (7.4%) 522,267 (28%) 2,186,820 (38%) 2,243,131 (43%) <0.001 Hyperlipidemia 8,218,876 (50%) 1,419,250 (31%) 818,576 (45%) 3,190,193 (61%) 2,790,857 (58%) 0.001 Hypertension 9,199,546 (49%) 1,446,937 (25%) 720,444 (39%) 2,947,894 (51%) 4,084,272 (78%) <0.001 Diabetes Mellitus 2,979,472 (16%) 163,139 (2.8%) 27,119 (1.5%) 1,178,643 (20%) 1,610,571 (31%) <0.001 Cancer site 0.025 Breast 2,330,094 (12%) 469,564 (8.0%) 203,473 (11%) 926,618 (16%) 730,438 (14%) Cervix 1,658,291 (8.9%) 1,152,755 (20%) 78,077 (4.2%) 296,026 (5.1%) 131,432 (2.5%) Colon 1,154,471 (6.2%) 191,595 (3.3%) 91,373 (4.9%) 250,311 (4.3%) 621,193 (12%) Melanoma 891,882 (4.8%) 344,435 (5.9%) 57,399 (3.1%) 207,468 (3.6%) 282,580 (5.4%) Prostate 1,695,376 (9.1%) 298,369 (5.1%) 70,991 (3.8%) 548,467 (9.4%) 777,549 (15%) Skin (others) 6,619,445 (35%) 1,816,354 (31%) 760,567 (41%) 2,515,424 (43%) 1,527,100 (29%) Uterus 597,856 (3.2%) 239,214 (4.1%) 91,014 (4.9%) 212,110 (3.6%) 55,519 (1.1%) Others 3,774,919 (20%) 1,321,756 (23%) 509,704 (27%) 856,429 (15%) 1,087,029 (21%) 1Median (Q1, Q3), n (%) 2Design-based KruskalWallis test, Pearson's X^2: Rao & Scott adjustmentAbstract 7-006 Table 2Survey-weighted multivariable-adjusted HR for all-cause & CV mortality associated with baseline CV risk according to PREVENT equations All-Cause Mortality Cardiovascular Mortality Baseline CV risk category aHR 1 95% CI 1 p-value sHR 1 95% CI 1 p-value Low Reference - - Reference - - Borderline-intermediate 4.38 2.48 - 7.74 <0.001 0.93 0.16 - 5.56 0.94 High 15.60 8.45 - 28.82 <0.001 14.01 3.37 - 58.26 <0.001 Per 5% increase in PREVENT Score 1.36 1.30 - 1.42 <0.001 1.50 1.35 – 1.66 <0.001 1aHR = Adjusted Hazard Ratio, CI = Confidence Interval. sHR= subdistribution Hazard Ratio. Adjusted to -family income, education level, and cancer site. Abstract 7-006 Figure 1Survey-weighted Kaplan-Meier (KM) survival curves by baseline CV risk categories according to PREVENT equations in NHANES (2013–2018) Cancer Population for a) all-cause mortality, and b) CV mortality. P-value for log-rank (< 0.01)",
  "authors": [
    {
      "affiliations": [
        "Keele University"
      ],
      "name": "Mustafa Al-Jarshawi"
    },
    {
      "affiliations": [
        "Keele University"
      ],
      "name": "Ofer Kobo"
    },
    {
      "affiliations": [
        "Schulich Heart Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada"
      ],
      "name": "Dennis T Ko"
    },
    {
      "affiliations": [
        "Schulich Heart Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada"
      ],
      "name": "Harindra C Wijeysundera"
    },
    {
      "affiliations": [
        "National Institute of Cardiovascular Diseases (NICVD), Dhaka, Bangladesh"
      ],
      "name": "M Golam Azam"
    },
    {
      "affiliations": [
        "Keele University"
      ],
      "name": "Victoria Silverwood"
    },
    {
      "affiliations": [
        "Keele University"
      ],
      "name": "Ram Bajpai"
    },
    {
      "affiliations": [
        "London Health Sciences Centre, Western University, London, Ontario, Canada"
      ],
      "name": "Rodrigo Bagur"
    }
  ],
  "title": "7-006 The prognostic value of the american heart association prevent cardiovascular disease risk equations in cancer survivorship: a nhanes population-based study (2009–2018)",
  "uid": "c79d7ab1-5625-5e86-9dc4-a0f6c9285e4f"
}