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Abstract

Importance:

Patients with a primary cutaneous melanoma (PCM) are at increased risk of developing a second primary melanoma (SPM). Earlier stage at diagnosis is associated with better 5-year mortality, yet low compliance with recommended follow-up after treatment for PCM and high rates of patients lost to follow-up are reported in the literature. Strategies to enhance population-based surveillance for SPM have not been well described.

Objective:

To determine whether the implementation of a systematic automated population-based program (SAPP) to ensure dermatologist total body skin exams (TBSEs) in the PCM population compared to the pre-automated period and pre-database periods improves compliance with follow-up, detects more SPMs, or affects mortality?

Design:

Quality Improvement Study.

Setting:

Large integrated health care system with internalized Dermatology services.

Participants:

Members with a PCM prior to, or during the study periods of interest, were included in this quality improvement study. There were 6317 eligible individuals with PCMs in 3 study periods: pre-Database (1/1/2005-11/1/2009), pre-Automation (11/1/09-7/31/15), and post-Automation (8/1/15-12/31/2021), respectively.

Intervention(s) or Exposure(s):

Manual registry for melanoma patients (pre-Automation) and systematic automated population-based program for PCM patients (post-Automation).

Main Outcome(s) and Measure(s):

Mean number of TBSE per person-year. Time Between TBSE. Incidence of SPM detection. Stage of SPM at diagnosis. Melanoma Death and All-Cause Mortality.

Results:

In patients with PCM, a SAPP to ensure dermatologist TBSE, reduces median time (months) between TBSEs from 12.3 pre-Database to 8.2 post-Automation (stage 0-2a PCM) and from 10.3 to 6.8 (stage 2b-4 PCM; P < .0001), improves number of TBSEs per person-year with each successive study period (pre-Database mean [SD] 0.56 [1.07]; pre-Automation 0.80 [1.25]; post-Automation 1.78 [4.17]; P < .0001), and improves SPM detection rates per 1000 person-years (pre-Database 20.2 [95% CI 12.2-30.9]; pre-Automation 27.5 [18.2-39.9]; post-Automation 27.5 [26.6-51.8], P < .0001 for trend) at earlier cancer stages. There is an associated annual reduction in all-cause (1.4 per 1000 person-years, P = .0004) and melanoma-cause mortality (0.2 per 1000 person-years, P = .0197).

Conclusion:

Implementing a systematic, automated population-based Melanoma program to ensure dermatologist TBSEs improves compliance with follow-up in patients with PCM. More patients received at least annual dermatologist TBSEs and more SPMs were detected at earlier stages. Improvements were sustained and there were significantly lower all-cause and melanoma-cause mortality. The system facilitates prioritization of higher risk patients for intervention and is a unique strategy enhancing patient safety, efficiency, and timeliness of care.

Keywords

cutaneous melanoma melanoma screening surveillance second primary melanoma total body skin examination

Introduction

The incidence of cutaneous melanoma has been increasing in the United States over the last 40 years. In 2024, there are 100 640 projected new cases of melanoma and 8290 estimated deaths in the United States.^1,2 The global burden of melanoma is increasing, estimated to be 510 000 new cases and 96 000 deaths by 2040.^2
-4 Cutaneous melanoma accounts for the majority of skin cancer mortality, up to 90% in the United States.^1,5
-7 Five-year survival correlates with melanoma stage at diagnosis: stage 1 is 98.4 %, stage 2 is 82.5%, stage 3 is 66.4%, and 14.4% for stage 4.⁸ Although there is no consensus for optimal frequency and duration of surveillance after PCM, multiple guidelines recommend lifelong skin surveillance by a health care practitioner.⁹

Individuals with a previous history of melanoma are at risk for developing second primary melanomas.^9
-14 The rate of second primary melanoma occurrence varies across the literature from 2% to 20%, typically within 5 years following diagnosis, highlighting the importance of timely follow-up.^10-11,14
-23 Low compliance with recommended follow-up and highly variable rates of surveillance after treatment for PCM are reported in the literature.^24
-30

Dermatologist total body skin exams (TBSEs) can detect melanoma recurrence and may lead to earlier detection of a SPM.^9,31
-35 An increase in melanoma mortality risk is associated with increasing tumor thickness (Breslow depth) and varies with cancer stage.^23,36,37 To determine whether a systematic, automated population-based program (SAPP) to ensure TBSE at least annually improves SPM detection rates, detects SPMs at earlier stages of diagnosis, and affects mortality, this study conducted an analysis of patients with cutaneous melanoma over 3 study periods.

Methods

Study Population and Surveillance Program

Eligible patients for this quality improvement study were enrolled in a large integrated healthcare system, and diagnosed with PCM prior to, or during the study periods of interest. Melanoma diagnosis was confirmed from pathology reports. The study is divided into 3 study periods: pre-Database between January 1, 2005 and October 31, 2009 represent baseline data when PCM patients were given usual future appointments after pathologic diagnosis; pre-Automation between November 1, 2009 and July 31, 2015 when a manual registry was used to track PCM patients overdue for TBSEs; and post-Automation between August 1, 2015 and December 31, 2021 when a Melanoma TBSE automated systematic program was implemented to ensure appropriate follow-up.

In December 2014, a multidisciplinary team developed the Melanoma TBSE automated program, utilizing key elements from the electronic medical record (EMR). The Dermatology department determines interval follow-up based on the National Comprehensive Cancer Network (NCCN) Guideline Recommendations for low-risk and high-risk melanoma stages.³⁸ Utilizing automated monthly reports, Dermatology staff actively outreach to patients with no future appointment within 6 months of the expected date. Workflows ensure completion of the appointment, and all patients are monitored until documented process completion, including shared decision-making to stop surveillance, transfer of surveillance to another health care system, or death.

Measurements

Primary outcomes of interest included (1) mean number of TBSE per person-year of follow-up, (2) time between TBSE, (3) incidence of SPM detection, (4) stage of SPM at diagnosis, and (5) melanoma deaths and all-cause mortality. Other outcomes of interest included (1) median Breslow depth of SPM, and (2) median time between TBSE among low risk (stages 0-2a) and high risk (stages 2b-4) individuals with PCM.

All primary and secondary tumors were identified using the ICD-O-3 site codes (C44.0-C44.9, C51.0-C51.2, C51.8, C51.9,C60.0-C60.2, C60.8, C60.9, and C63.2) for melanoma in the organization’s tumor registry. The tumor registry contains all cancer patients diagnosed since 1990 and the morphological characteristics of the tumors. It follows the format of the Facility Oncology Registry Data Standards (FORDS): Revised for 2004; the staging rules are those defined by the Collaborative Staging Task Force of the American Joint Committee on Cancer.³⁹

The primary tumor is the first primary melanoma listed in the registry for each patient. To confirm that the tumor is a primary, we searched the diagnoses and problem lists from the EMR for any melanomas occurring prior to the identified primary tumor. If a patient had a melanoma diagnosis (ICD-9 172; ICD-10 C43; or D03) or noted history of melanoma (ICD-9 V10.82; ICD-10 Z85.820) prior to the first tumor in the tumor registry, that patient was excluded from the analyses. Second primary melanomas include any primary melanoma in the tumor registry that was diagnosed after the first primary and during one of the study periods.

Demographic information including self-reported race/ethnicity was obtained from the EMR. Due to small representation of several races, we used 4 race groups for persons with PCM: Asian, White, more than 1 race, and other/unknown. For persons with SPM, we further collapsed into White and non-White groups. Date of death is obtained from membership, patient encounter data and state death records. Cause of death is obtained from the CDC National Death Index (NDI) as part of an agreement that it is solely used for statistical purposes in medical research. The NDI data are matched to our members annually and are current through 2019. Thus, we have all-cause mortality through study end and melanoma-cause mortality through 2019. Due to the COVID-19 pandemic, the mortality analysis did not include 2020 to 2021 data.

Statistical Methods

Person-months (years) of follow-up were calculated for each patient and used as the denominator for SPM incidence, TBSE and mortality rates. These were left- or right-censored based on date of PCM, health plan enrollment/disenrollment, or death, if applicable. As participants had varying numbers of TBSE during the study periods, we calculated the average time between successive TBSEs for each participant and compared the median of these averages between groups.

Demographic and outcome characteristics were compared between the 3 study periods using ANOVA for continuous measures and either chi-square or Fisher’s Exact tests for categorical measures as appropriate. For outcomes that were not normally distributed (eg, Breslow depth), the nonparametric Kruskal-Wallis test was used for group comparisons. When the overall group comparisons were statistically significant (P < .05), we analyzed pairwise group differences using Bonferroni, Tukey-Kramer and Dwass-Steel-Critchlow-Fligner methods to adjust for multiple comparisons. In addition to group comparisons, we tested for trends in outcomes by year using Poisson, logistic, and quantile regression as appropriate. All statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary NC).

Results

Overall, 1327 individuals in the pre-Database period, 1958 individuals in the pre-Automation period, and 3032 individuals in the post-Automation period were identified as eligible for inclusion in this study. At baseline, average age at PCM diagnosis was approximately 2 years greater with each successive study period (P < .0001). The race/ethnic distribution at baseline also differed (P < .0001), largely driven by more White patients in pre- and post-automation study periods (see appendix Table A1).

The mean number of TBSEs per person-year increased across the 3 time periods (P < .0001, Table 1). Further, the percentage of patients with at least 1 TBSE per year has steadily increased over the study periods (P < .0001, Figure 1). The intervals between follow-up TBSE were lower in the post-Automation period compared to 2 prior periods, a difference which persisted when stratified by low risk (0-2a) and high risk (2b-4) PCM stage (P < .0001, Table 1).

Table 1.

Follow-up Surveillance, Incidence, and Characteristics of Second Primary Melanoma, by Study Period.

	Pre-database January 2005 to October 2009 (n = 1327)	Pre-automation November 2009 to July 2015 (n = 1958)	Post-automation August 2015 to December 2021 (n = 3032)	P-value^a
Follow-up surveillance
Months of follow-up per person^b: mean(sd)	39.3 (20.4)	41.2 (25.7)	47.4 (27.1)
Number with at least 1 annual Follow-up TBSE: n(%)	681 (51.3)	1237 (63.2)	2605 (85.9)	<.0001
Number of TBSE per person-year: mean (sd)	0.56 (1.07)	0.80 (1.25)	1.78 (4.17)	<.0001
Time (months) between TBSE by Stage-based Risk^c: median(IQR)
Stage 0-2a	12.4 (8.0-22.6)	12.8 (7.9-22.2)	8.2 (6.6-11.7)	<.0001
Stabe 2b-4	10.3 (7.2-22.4)	10.6 (8.3-15.9)	6.8 (4.7-11.2)
Incidence (95% CI) second primary melanoma per 1000 person-years	20.2 (12.2-30.9)	27.5 (18.2-39.9)	37.7 (26.6-51.8)	<.0001
Number of second primary melanoma: n (%)
0	1240 (93.4)	1771 (90.6)	2661 (85.5)	<.0001
1	72 (5.4)	153 (7.8)	344 (11.1)
2 or more	15 (1.1)	32 (1.6)	107 (3.4)
Characteristics of patients with second primary melanoma
Sex at birth: n(%)
Male	56 (64.4)	118 (63.8)	307 (68.1)	.5246
Female	31 (35.6)	67 (36.2)	144 (31.9)
Race/ethnicity: n(%)
White	78 (89.7)	174 (94.1)	417 (92.5)
Non-white^d	9 (10.3)	11 (5.9)	34 (7.5)
Characteristics of second primary melanoma
Breslow depth (mm): median (IQR)	0.48 (0.28-0.87)	0.22 (0-0.45)	0.02 (0-0.20)	<.0001
Stage^e
0-2a	73 (93.6)	162 (93.6)	430 (97.5)	.0403
2b-4	5 (6.4)	11 (6.4)	11 (2.5)

P-values based on chi-square or Fisher’s Exact test for categorical measures and ANOVA or Kruskall-Wallis test for continuous measures. A P-value comparing person-months of follow-up is not calculated as study periods differ in length.

Months of follow-up vary by individual based on when the primary tumor was diagnosed, health-plan enrollment/disenrollment, and death. Maximum months of follow-up is the length of each study period.

Stage-based risk is the stage of the baseline primary cutaneous melanoma.

Non-white include Asian, American Indian, Alaska Native, Native Hawaiian, Other Pacific Islander, Black or African American, persons reporting more than 1 race, or individuals who have not self-reported their race.

Stage of cancer was not available for 9 pre-database, 12 in pre-automation, and 10 in post-automation period.

Figure 1.

Patients with at least 1 TBSE per year (%).

Significantly more SPMs were detected in the post-Automation period at a lower median Breslow depth (median = 0.02 mm) compared to the previous 2 study periods (0.48 mm pre-Database; 0.22 mm pre-Automation; P < .0001; Table 1, Figure 2). Progressively more SPMs per 1000 person-years were detected through the study periods, with a notable decline in 2020 to 2021 (P = .0143; Table 1, Figure 3). With each successive study period, there has also been increased detection of early-stage SPMs (Table 1, Figure 4 (P = .0013)). Rates of melanoma-specific mortality have significantly decreased over time (P = .0197; Figure 5). Non-melanoma (P = .0050) and all-cause mortality (P = .0004) also significantly decreased between 2005 and 2019 (Figure 5).

Figure 2.

Breslow depth of second primary melanomas.

Figure 3.

Second primary melanomas per 1000 person-years.

Figure 4.

Stage of second primary melanoma by study period.

Figure 5.

Melanoma and non-melanoma deaths among persons with primary melanoma.

Due to increase in mortality related to the COVID-19 pandemic, and because we have melanoma mortality data through 2019, we estimated mortality trends from 2005 to 2019. P-values for trend are .0197 for melanoma mortality, .0050 for non-melanoma mortality, and .0004 for all-cause mortality (sum of blue and green bars). Pairwise group comparisons are all non-significant.

Discussion

Strategies to enhance population-based surveillance for SPM have not been well described in the literature. In a Veterans Health Administration study, non-automated phone reminders after surgical excision or Mohs surgery, increased compliance with TBSE follow-up only in the Mohs surgery group.⁴⁰ In our study conducted over 3 study periods, each spanning at least 5 years, we compared increasingly reliable interventions to ensure appropriate follow-up for patients with PCM. The Melanoma program facilitates early detection of SPM and enhances patient safety by consistently managing a high-risk population. Proactive outreach assures appropriate dermatologist TBSE and those who are unable to complete an appointment have specified outreach interventions to enhance safety. Since the implementation of the Melanoma program (post-Automation period), dermatology follow-up has been timelier—with significantly greater mean TBSEs per person-year, more frequent interval follow-ups, and increased percentage of PCM patients with at least annual TBSE compared to earlier time periods. The time between successive TBSEs was significantly lower in the post-automation group compared to both the pre-database and pre-automation groups highlighting the capability to prospectively prioritize patient outreach, not evident in earlier time periods.

Between 2006 and 2019, SPMs per 1000 person-years were up-trending, likely due to increased detection and consistent with epidemiologic reports of increasing melanoma incidence (Figure 3).^1,2 As more SPMs were detected, they were also found to be progressively thinner, as measured by Breslow depth, and corresponded with significantly more stage 0 SPMs, consistent with published literature.^{15,19,22,41,42} This finding in combination with the progressive decline in the total stages 1 to 4 SPMs across the study periods suggests detection of cancer at earlier stages and improved prognosis for those managed by the Melanoma program.^19,43,44 These data are consistent with Commission on Cancer benchmark data for melanoma stage at diagnosis showing this organization detecting many more stage 0 melanomas over time and progressively fewer stage 1 to 4 cancers compared to other accredited US facilities between 2012 and 2019.⁴⁵

Between 2005 and 2019, we found a significant reduction in both melanoma-specific and all-cause mortality in the higher-risk PCM population managed by the SAPP. Large population-based skin screenings have resulted in a sharp increase in melanoma diagnosis, particularly stage 0 melanoma, without any effect on mortality. This has led to discussions in the literature of over-diagnosis of melanoma.^{19,36,41,46
-51} However, a recent study reported melanoma-specific mortality associated with a diagnosis of stage 0 melanoma (15-year melanoma-specific survival 98.4%) is similar to that for very thin invasive melanoma (Stage T1a).^50,52,53 In this same study, the 15-year risk of developing a subsequent primary invasive melanoma was 8.9% and 14.1% for a second primary stage 0 melanoma.⁴⁸ Diagnosis of a subsequent primary invasive melanoma was associated with worse melanoma-specific survival (91.1%), but not with a second primary stage 0 melanoma (98.2%). As expected, the earlier the stage of the second primary melanoma detection, the better the prognosis. Due to the increasing detection of stage 0 melanomas in this study, future refinements to the Melanoma Program for MIS may be warranted.⁵⁰

The decline in SPM detection, the slight increase in SPM Breslow depth, and the increase in all-cause mortality in 2020 to 2021 all coincided with the onset of the COVID-19 pandemic. During the pandemic, this state issued a stay-at-home order, likely leading to the reluctance to seek in-person care required for TBSE.⁵⁴ This observation is consistent with published reviews showing decreased new diagnoses of melanoma and non-melanoma skin cancers compared to baseline during the pandemic.⁵⁵

The demographics of members in this study mirror state-wide racial demographic characteristics, which include larger proportions of Asian, Native Hawaiian, Pacific Islander, and multiracial populations. While melanoma incidence has been reported to be increasing across all races, there is higher detection of SPM in the White and multiracial populations and stable rates in Native Hawaiian, Pacific Islander and Asian populations.⁵⁶ Further research is needed to determine the effects that race, disparities in care, and/or changing incidence of disease may have on SPMs.

A strength of our study is that all participants are enrolled in an integrated system of insured patients for which diagnostic reliability is enhanced by enabling appropriate monitoring. Data were collected as a part of clinical care and recorded consistently within the EMR reducing common ascertainment biases. Because the study was conducted within our local organization, findings may not be generalizable to other populations with differing demographic characteristics. Further, this quality improvement study mimics a retrospective cohort study and may be subject to attrition bias. The translatability of this systematic program to other less integrated systems will need to be evaluated.

Conclusion

Implementing a systematic, automated population-based Melanoma TBSE program to ensure dermatologist TBSEs improves compliance with follow-up in patients with PCM. More patients received at least annual dermatologist TBSEs and more second primary melanomas were detected at earlier stages. Improvements were sustained over time and there was an association with reduced melanoma-cause and all-cause mortality. The system facilitates prioritization of higher risk patients for intervention and is a unique strategy designed to enhance patient safety, efficiency, and timeliness of care.

Footnotes

Appendix

Table A1.

Demographic and Clinical Characteristics of Patients With Primary Cutaneous Melanoma, By Study Period.

	Pre-database January 2005 to October 2009 (n = 1327)	Pre-automation November 2009 to July 2015 (n = 1958)	Post-automation August 2015 to December 2021 (n = 3032)	P-value^a
Patient characteristics
Months of follow-up per person^b: mean (SD)	39.3 (20.4)	41.2 (25.7)	47.4 (27.1)
Sex at birth: n (%)
Male	759 (57.2)	1116 (57.0)	1752 (57.8)	.8461
Female	568 (42.8)	842 (43.0)	1280 (42.2)
Race/ethnicity: n (%)
Asian	57 (4.3)	36 (1.8)	35 (1.1)	<.0001
White	1063 (80.1)	1632 (83.4)	2580 (85.1)
More than 1 race	175 (13.2)	243 (12.4)	333 (11.0)
Other/unknown^c	32 (2.41)	47 (2.4)	84 (2.8)
Age of patient at first primary melanoma: mean (SD)	56.7 (15.1)	58.6 (14.7)	60.8(14.1)	<.0001
Characteristics of primary cutaneous melanoma
Breslow depth (mm): median (IQR)	0.23 (0.04-0.60)	0.28 (0.03-0.63)	0.14 (0.00-0.47)	<.0001
Diameter (mm):median (IQR)	0.006 (0.003-0.012)	0.007 (0.004-0.011)	0.007 (0.005-0.010)	<.0001
Stage^d
0-2a	935 (93.2)	1469 (95.3)	2586 (96.7)	<.0001
2b-4	68 (6.8)	73 (4.7)	88 (3.3)

P-values based on chi-square test for categorical measures and ANOVA for continuous measures except for Breslow depth and diameter for which the Kruskal-Wallis test was used due to non-normal distribution. A P-value comparing person-months of follow-up is not calculated as study periods differ in length.

Months of follow-up vary by individual based on when the primary turn or was diagnosed, health-plan enrollment/disenrollment, and death. Maximum months of follow-up is the length of each study period.

Other/unknown include American Indian, Alaska Native, Native Hawaiian, Other Pacific Islander, Black or African American, or individuals who have not self-reported their race.

Stage of cancer was not available for 324 pre-database, 416 in pre-automation, and 358 in post-automation period.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Allison Ching

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