Progression-free survival and overall survival after BRCA1/2-associated epithelial ovarian cancer: A matched cohort study.

INTRODUCTION: Germline BRCA1/2-associated epithelial ovarian cancer has been associated with better progression-free survival and overall survival than sporadic epithelial ovarian cancer, but conclusive data are lacking.
METHODS: We matched 389 BRCA1-associated and 123 BRCA2-associated epithelial ovarian cancer patients 1:1 to sporadic epithelial ovarian cancer patients on year of birth, year of diagnosis, and FIGO stage (< = IIA/> = IIB). Germline DNA test was performed before or after epithelial ovarian cancer diagnosis. All patients received chemotherapy. We used Cox proportional hazards models to estimate the associations between mutation status (BRCA1 or BRCA2 versus sporadic) and progression-free survival and overall survival. To investigate whether DNA testing after epithelial ovarian cancer diagnosis resulted in survival bias, we performed additional analyses limited to BRCA1/2-associated epithelial ovarian cancer patients with a DNA test result before cancer diagnosis (n = 73 BRCA1; n = 9 BRCA2) and their matched sporadic controls.
RESULTS: The median follow-up was 4.4 years (range 0.1-30.1). During the first three years after epithelial ovarian cancer diagnosis, progression-free survival was better for BRCA1 (HR 0.88, 95% CI 0.74-1.04) and BRCA2 (HR 0.58, 95% CI 0.41-0.81) patients than for sporadic patients. Overall survival was better during the first six years after epithelial ovarian cancer for BRCA1 (HR 0.7, 95% CI 0.58-0.84) and BRCA2 (HR 0.41, 95% CI 0.29-0.59) patients. After surviving these years, survival benefits disappeared or were in favor of the sporadic patients.
CONCLUSION: For epithelial ovarian cancer patients who received chemotherapy, we confirmed survival benefit for BRCA1 and BRCA2 germline pathogenic variant carriers. This may indicate higher sensitivity to chemotherapy, both in first line treatment and in the recurrent setting. The observed benefit appears to be limited to a relatively short period after epithelial ovarian cancer diagnosis.

Introduction

Despite a relatively low cumulative life-time risk–~1.6% for women in the western world–ovarian cancer is the fifth most common cause of cancer death in women, with worldwide over 150,000 deaths each year [1, 2]. The high mortality rate is largely due to the tendency to early spreading in the abdominal cavity, and most ovarian cancers being diagnosed at advanced stages (FIGO stage III/IV) [3-5]. Despite a high response rate to platinum-based chemotherapy, the overall survival (OS) remains poor with a 5-year overall survival of only 30–40% [3, 4].

Approximately 11–15% of all epithelial ovarian cancer (EOC) patients carry a BRCA1 or BRCA2 germline pathogenic variant (gPV) [6-10]. Women with a BRCA gPV have a high cumulative life-time risk of developing EOC, being 40–60% for BRCA1 and 10–25% for BRCA2 gPV carriers [11-15]. In general, EOC in BRCA gPV carriers is diagnosed at a younger age than in sporadic patients, and younger in BRCA1 gPV carriers than in BRCA2 gPV carriers [11-16]. In view of the absence of effective screening for EOC, women with a proven BRCA gPV are advised to opt for premenopausal risk-reducing salpingo-oophorectomy at the age of 35 to 40 years for BRCA1 gPV carriers and 40 to 45 years for BRCA2 gPV carriers.

BRCA-deficiency is associated with an impaired ability to repair double-strand DNA breaks by the DNA repair mechanism homologous recombination [17-21]. This may lead to higher response rates to first-line platinum-based chemotherapy–which causes double-strand DNA breaks–and thus to improved survival [22-24]. Indeed, some studies have reported better survival for BRCA-associated EOC patients than for sporadic patients [10, 22–26], although the reported results are not consistent [27-29]. Survival benefit may be limited to BRCA2 gPV carriers [30], or only applicable to the first five to ten years [31-33]. A few studies showed also higher response rates to platinum-based chemotherapy after recurrent EOC in BRCA gPV carriers than in sporadic EOC patients, but the numbers of included patients are small [10, 24, 34]. Further, the sensitivity to platinum-based chemotherapy might depend on the associated gene and/or the specific pathogenic variant [28, 30].

Altogether, definitive evidence of better prognosis for BRCA-associated EOC patients is still unavailable. Moreover, while BRCA1 and BRCA2 tumors might represent different entities, most studies did not investigate prognosis and survival after EOC separately for BRCA1 and BRCA2. In the current retrospective cohort study we compare progression-free survival (PFS) and overall survival (OS) between either germline BRCA1-associated EOC patients or germline BRCA2-associated EOC patients and matched sporadic EOC patients treated with first-line chemotherapy.

Participants and methods

Study population

For this retrospective matched cohort study, we selected BRCA1 and BRCA2 gPV carriers with a history of EOC from the national Hereditary Breast and Ovarian Cancer Netherlands (HEBON) database. In the context of the HEBON study, members of breast and/or ovarian cancer families are being identified through the departments of Clinical Genetics/Family Cancer Clinics at eight Dutch academic centers and the Netherlands Cancer Institute [35]. The study was approved by the Medical Ethical Committees of all participating centers. Written informed consent was obtained from each participant or from a close relative in case of deceased individuals. Relevant data on participants including data on preventive strategies, the occurrence of cancer, and vital status were retrieved and updated through medical files and questionnaires, and through linkages to the Netherlands Cancer Registry, the Dutch Pathology Database, and the municipal registry database. The latest follow-up date was December 31, 2017.

From this national cohort, we selected 389 BRCA1 gPV carriers and 123 BRCA2 gPV carriers with EOC. Patients were eligible for the study if they were diagnosed with EOC after 1988, had a proven BRCA gPV (with DNA test result either before or after EOC diagnosis), and received chemotherapy after diagnosis of primary EOC (in case of surgery, either before or after).

The selected BRCA gPV carriers were matched 1:1 to sporadic EOC patients from the National Cancer Registry on year of birth (+/– 5 years), year of EOC diagnosis (+/- 5 years), and FIGO stage (≤IIA/≥IIB/unknown). Sporadic patients were defined as patients who were either not DNA tested due to a negative family history of breast cancer or ovarian cancer or because DNA testing was not available yet, or DNA tested and without a proven BRCA gPV. Notably, about 5% of EOCs have a somatic BRCA pathogenic variant, but somatic testing has only been widely implied since 2020 in the Netherlands and data hereon is therefore not available for the current cohort.

Data collection

We retrieved data on the associated gene (i.e. BRCA1 or BRCA2) and date of DNA test result, dates of birth and death, and dates of diagnosis of EOC, first recurrent disease, and other cancers. We also collected data on tumor characteristics (FIGO stage, histology, and differentiation grade), CA125 at EOC diagnosis, and treatment details after primary EOC diagnosis and in the recurrent setting (surgery, type of chemotherapy, and maintenance treatment with poly(ADP-ribose) polymerase inhibitors (PARPi)).

Statistical analyses

We evaluated clinical characteristics by comparing EOC patients with (BRCA1 and BRCA2 groups) and without a proven BRCA gPV (sporadic groups). We used Pearson’s chi-squared test for differences between the BRCA groups and the sporadic groups for categorical variables, and Wilcoxon rank-sum to test the equality of the medians for continuous variables.

The outcomes PFS and OS were measured in person-years of observation. The observation period started at the date of EOC diagnosis, and ended at the date of a censoring event or the date of first recurrence for the PFS analyses or death for the OS analyses. Censoring events included diagnosis of a new primary malignant tumor, date of last follow-up, and date of death (for PFS only).

To estimate the associations between gPV status (BRCA1 or BRCA2 versus sporadic) and survival endpoints, we used Cox proportional hazards models with the sporadic groups as the references to obtain hazard ratios (HR) with corresponding 95% confidence intervals (CI). We considered age at EOC diagnosis, grade, CA125 at diagnosis, type of chemotherapy, debulking surgery (yes/no), and complete debulking surgery (yes/no, i.e. the absence/presence of any residual disease) as potential confounders. The matching variables year of birth, year of EOC diagnosis, and FIGO stage were by definition not confounding factors. We generated Kaplan-Meier survival curves, and used the log-rank test for equality of survivor functions to test whether the curves were significantly different from each other. We performed all analyses separately for BRCA1 and BRCA2 gPV carriers.

Further, BRCA gPV carriers who underwent DNA testing after EOC diagnosis survived at least until this DNA test, which was in some cases many years after EOC diagnosis. To investigate whether this resulted in survival bias in favor of the BRCA gPV carriers, we also performed prospective analyses limited to BRCA-associated EOC patients with a DNA test result before EOC diagnosis and their matched sporadic controls.

Furthermore, as previous studies reported different short-term and long-term survival rates for gPV carriers [31-33], the proportional hazards assumption may be violated. Therefore we used Schoenfeld residuals to test whether the proportional hazards assumption is violated. If that was the case, we stratified the Cox models by a specified time-of-observation, i.e. the moment t where the HR switched from under 1 to above 1 (or vice versa). We calculated this exact moment using the formula where x is the variable of interest (i.e. BRCA1/BRCA2 or sporadic), β is the β coefficient, and δ is the time-varying coefficient. When the proportional hazards assumption is valid, δ equals zero. Otherwise, we can calculate t using

HR(t) = 1

⇨ ln(HR(t)) = 0

⇨ ln(exp(βx + δxt)) = 0

⇨ βx + δxt = 0

⇨ t = -β / δ

where β and δ are derived from the Cox model including both the variable for gPV status and the interaction term of this variable with time.

All p-values were two-sided, and a significance level α = 0.05 was used. Analyses were performed using Stata/SE (version 16.0, StataCorp, Collegestation, TX).

Results

As shown in Table 1, the 389 BRCA1 gPV carriers and the 123 BRCA2 gPV carriers had longer follow-up than their matched sporadic EOC patients (median years 4.8 versus 3.5 for the BRCA1 comparison, p<0.001; 5.7 versus 3.5 for the BRCA2 comparison, p<0.001). The vast majority of the patients received platinum-based chemotherapy. After recurrence of disease, BRCA1-associated EOC patients were treated more often with chemotherapy than the sporadic patients (90% versus 79%, p<0.001), which did not apply for the BRCA2 comparison (Table 1). The characteristics for the dataset used for the prospective analyses (in total n = 82 matched pairs) are shown in S1 Table.

Table 1

Patient and tumor characteristics.

	BRCA1		Sporadic			BRCA2		Sporadic
	N	%	N	%	p-value	N	%	N	%	p-value
	389		389			123		123
Follow-up, median years (range)	4.8	(0.1–26.7)	3.5	0.1–30.1	<0.001	5.7	(0.5–25.6)	3.5	(0.1–24.1)	<0.001
Year of birth, median (range)	1950	(1922–1981)	1950	(1922–1979)	.757	1946	(1923–1972)	1946	(1922–1972)	.824
DNA test result
Median age, median (range)	54	(26–81)				61	(35–79)
Time between EOC diagnosis and DNA test result, median years (range)	1	(0–19.8)				1.1	(0–16.3)
before EOC	72	(19%)				8	(7%)
<6 months	46	(12%)				19	(15%)
6–12 months	74	(19%)				24	(20%)
1–3 years	117	(30%)				38	(31%)
3–5 years	28	(7%)				15	(12%)
5–10 years	34	(9%)				11	(9%)
>10 years	17	(4%)				7	(6%)
unknown	1	(0%)				1	(1%)
Year of EOC diagnosis, median (range)	2004	(1989–2015)	2004	(1989–2014)	.726	2004	(1989–2014)	2005	(1989–2014)	.558
Age at EOC diagnosis, median (range)	52	(23–78)	52	(23–77)	.488	58	(35–76)	57	(35–79)	.888
FIGO
Low (≤IIA)	34	(10%)	46	(13%)	.151	16	(14%)	19	(17%)	.522
High (≥IIB)	323	(90%)	310	(87%)		96	(86%)	90	(83%)
unknown	32		33			11		14
Grade
Well differentiated	9	(3%)	32	(11%)	<0.05	1	(1%)	5	(5%)	.088
Poorly differentiated	320	(97%)	261	(89%)		102	(99%)	94	(95%)
unknown	60		96			14		24
Histology
Serous	282	(73%)	224	(58%)	<0.001	81	(67%)	81	(66%)	.546
Endometrioid	30	(8%)	53	(14%)		8	(7%)	15	(12%)
Clear cell	3	(1%)	23	(6%)		3	(2%)	3	(2%)
Mucinous	7	(2%)	18	(4%)		3	(2%)	5	(4%)
Adenocarcinoma NOS	52	(13%)	61	(16%)		24	(20%)	17	(14%)
Other	11	(3%)	8	(2%)		3	(2%)	2	(2%)
Unknown	4		2			1		0
CA125 (U/ml)
≤35	33	(12%)	19	(6%)	<0.01	4	(5%)	9	(9%)	.576
35–500	106	(37%)	148	(49%)		33	(41%)	38	(37%)
>500	147	(51%)	137	(45%)		44	(54%)	55	(54%)
unknown	103		85			42		21
Type of chemotherapy
platinum & anthracyclines	1	(0%)	2	(1%)	.527	0	(0%)	1	(1%)	.521
platinum & taxanen	313	(84%)	301	(83%)		102	(87%)	96	(81%)
platinum	52	(14%)	49	(13%)		14	(12%)	20	(17%)
taxanen & anthracyclines	1	(0%)	5	(1%)		0	(0%)	1	(1%)
taxanen	6	(2%)	6	(2%)		1	(1%)	1	(1%)
unknown	16		26			6		4
Timing of chemotherapy
Neoadjuvant	64	(18%)	83	(24%)	.051	35	(30%)	27	(24%)	.304
Adjuvant	299	(82%)	270	(76%)		82	(70%)	86	(76%)
unknown	26		36			6		10
Debulking surgery
No	10	(3%)	26	(7%)	<0.01	3	(2%)	7	(6%)	.201
Yes (primary or interval)	378	(97%)	354	(93%)		118	(98%)	115	(94%)
unknown	1		9			2		1
Complete debulking
No	127	(46%)	110	(47%)	.893	38	(48%)	34	(47%)	.851
Yes	149	(54%)	126	(53%)		41	(52%)	39	(53%)
unknown	102		118			39		42
Recurrent disease	299	(77%)	306	(79%)	.546	84	(68%)	92	(75%)	.258
Age at 1st recurrence, median (range)	54	(29–79)	55	(30–78)	.184	61	(35–79)	60	(37–79)	.817
Year of 1st recurrence, median (range)	2006	(1990–2017)	2006	(1989–2020)	.276	2007	(1994–2014)	2007	(1989–2019)	.828
Time between diagnosis of EOC and 1st recurrence, median months (range)	18.3	(0.6–179.3)	15.9	(0.5–364.3)	<0.005	22.3	(2.1–116.7)	15.7	(0.6–174.1)	<0.001
Before DNA test result	108	(36%)				31	(37%)
After DNA test result	191	(64%)				52	(63%)
Chemotherapy after recurrence
No	31	(10%)	56	(21%)	<0.001	11	(13%)	11	(14%)	.826
Yes	266	(90%)	206	(79%)		73	(87%)	66	(86%)
Unknown	2		44			0		15
PARPi after recurrence
No	269	(91%)	254	(98%)	<0.001	75	(91%)	69	(96%)	.272
Yes	25	(9%)	4	(2%)		7	(9%)	3	(4%)
Unknown	5		48			2		20
Deceased	274	(70%)	292	(75%)	.147	78	(63%)	91	(74%)	.074
Age at death, median (range)	57	(32–83)	56	(33–87)	.248	63	(36–89)	62	(38–82)	.121
Time between 1st recurrence and death, median months (range)	25.9	(0–166)	13.9	(0–156.1)	<0.001	25	(0.3–152.2)	15.3	(0–106.8)	<0.001
Time between diagnosis of EOC and death, median months (range)	49.2	(0.6–233.9)	33.4	(0.9–217.8)	<0.001	53	(9.3–254.7)	32.9	(0.6–277.6)	<0.001

Abbreviations: EOC, epithelial ovarian cancer; PARPi, poly(ADP-ribose) polymerase inhibitors.

Potential confounders

No differences between the groups were observed for the matching variables year of birth, year of EOC diagnosis, and FIGO stage, nor for age at EOC diagnosis and type of chemotherapy (Table 1). Due to the large proportion of missing data for CA125 at diagnosis, EOC grade, and completeness of debulking surgery, no adjustment was possible for these variables. We performed Cox models adjusted for debulking surgery (yes/no), with the sporadic groups as the references.

Survival analyses

We observed no differences between the BRCA-associated groups and their matched sporadic patients in the percentage of patients with recurrent disease. The time between diagnoses of EOC and first recurrence, though, was longer for BRCA-associated patients than for the sporadic patients (BRCA1 comparison: 18.3 versus 15.9 months, p<0.005; BRCA2 comparison: 22.3 versus 15.7 months, p<0.001; Table 1). Likewise, the percentages of deceased patients were similar in all comparison groups, while the time between diagnosis of first recurrence and death is longer for EOC patients with a BRCA gPV (BRCA1 comparison: 25.9 versus 13.9 months, p<0.001; BRCA2 comparison: 25 versus 15.3 months, p<0.001; Table 1).

As shown in Table 2, while BRCA1 gPV status was not associated with significant differences in PFS, the Cox model for OS yielded an HR of 0.82 (95% CI 0.7–0.97) in favor of BRCA1 gPV carriers. In addition, the prospective analyses–limited to BRCA1-associated EOC patients with a DNA test result before EOC diagnosis and their matched sporadic controls–showed better PFS (HR 0.65, 95% CI 0.43–0.97), but no significant OS benefit for BRCA1 gPV carriers (HR 0.86, 95% CI 0.56–1.3; Table 2). Accompanying survival curves are depicted in Fig 1. As the proportional hazards assumption was violated for all models, the analyses were stratified for the moment in time t where the HR equals 1. The stratified analyses revealed HRs under 1 when the observation time was shorter than t (varying from 3.1 to 6 years), and above 1 for longer observation time (Table 2).

Table 2

Association of BRCA1 germline pathogenic variant status with progression-free survival and overall survival.

	Progression-free survival					Overall survival
	N	PYO	Events	Rec. rate1 (95% CI)	HR (95% CI)2	N	PYO	Events	Mort. rate1 (95% CI)	HR (95% CI)2
Complete analyses
Total observation period
BRCA1	389	1475	299	203 (181–227)	0.9 (0.77–1.06)	389	2452	274	112 (99–126)	0.82 (0.7–0.97)
sporadic	389	1527	306	200 (179–224)	1	389	2244	292	130 (116–146)	1
Observation period < t	t = 3.3 yrs					t = 6 yrs
BRCA1	389	807	249	309 (273–349)	0.88 (0.74–1.04)	389	1702	206	121 (106–139)	0.7 (0.58–0.84)
sporadic	389	726	251	346 (305–391)	1	389	1416	251	177 (157–201)	1
Observation period ≥ t
BRCA1	124	668	50	75 (57–99)	1.01 (0.69–1.49)	150	751	68	91 (71–115)	1.61 (1.09–2.38)
sporadic	120	800	55	69 (53–90)	1	120	828	41	50 (36–67)	1
Prospective analyses
Total observation period
BRCA1	73	268	47	176 (132–234)	0.65 (0.43–0.97)	73	406	42	103 (76–140)	0.86 (0.56–1.3)
sporadic	73	252	55	218 (167–284)	1	73	380	47	124 (93–164)	1
Observation period < t	t = 3.1 yrs					t = 5.7 yrs
BRCA1	73	155	36	232 (168–322)	0.56 (0.36–0.88)	73	298	32	107 (76–152)	0.72 (0.45–1.15)
sporadic	73	131	46	351 (263–469)	1	73	264	41	155 (114–210)	1
Observation period ≥ t
BRCA1	31	113	11	97 (54–176)	1.15 (0.47–2.78)3	27	109	10	92 (50–171)	1.89 (0.67–5.31)3
sporadic	24	121	9	74 (39–176)	1	25	116	6	52 (23–116)	1

Abbreviations: N, number of patients; PYO, person-years of observation; Rec. rate, recurrence rate; Mort. Rate, mortality rate; HR, hazard ratio; 95% CI, 95% confidence interval; t, time point where HR switches from under to above 1 (in years of observation after diagnosis of epithelial ovarian cancer).

1 per 1000 PYO.

2 adjusted for debulking surgery (yes/no).

3 univariable analysis; adjusting for debulking surgery omitted due to zero patients without debulking surgery.

Fig 1

Kaplan-Meier survival curves for BRCA1-associated epithelial ovarian cancer (EOC) patients (dashed lines) and sporadic EOC patients (solid lines) treated with chemotherapy.

(A) progression-free survival and (B) overall survival for the complete dataset; (C) progression-free survival and (D) overall survival for the prospective dataset.

Overall, as shown in Table 3, BRCA2 gPV carriers showed better PFS (HR 0.67, 95% CI 0.5–0.91) and OS (HR 0.61, 95% CI 0.44–0.83) than their matched sporadic patients, which can also be seen in Fig 2. The stratified analyses revealed a significant risk-reduction in favor of BRCA2 gPV carriers for PFS (HR 0.58, 95% CI 0.41–0.81; Table 3) and OS (HR 0.41, 95% CI 0.29–0.59) for the observation period under t (being 3 and 6 years, respectively), but a higher risk for death after t (HR 3.14, 95% CI 1.34–7.34). The numbers of patients in the prospective analyses were too small to draw meaningful conclusions (Table 3 and Fig 2).

Table 3

Association of BRCA2 germline pathogenic variant status with progression-free survival and overall survival.

	Progression-free survival					Overall survival
	N	PYO	Events	Rec. rate1 (95% CI)	HR (95% CI)2	N	PYO	Events	Mort. rate1 (95% CI)	HR (95% CI)2
Complete analyses
Total observation period
BRCA2	123	538	84	156 (126–193)	0.67 (0.5–0.91)	123	882	78	88 (71–110)	0.61 (0.44–0.83)
sporadic	123	482	92	191 (156–234)	1	123	702	91	130 (105–159)	1
Observation period < t	t = 3 yrs					t = 6 yrs
BRCA2	123	269	65	242 (190–308)	0.58 (0.41–0.81)	123	570	52	91 (70–120)	0.41 (0.29–0.59)
sporadic	123	220	80	364 (292–453)	1	123	450	84	186 (151–231)	1
Observation period ≥ t
BRCA2	52	269	19	71 (45–111)	1.37 (0.66–2.83)3	57	312	26	83 (57–122)	3.14 (1.34–7.34)3
sporadic	38	262	12	45 (26–81)	1	34	252	7	28 (13–58)	1
Prospective analyses
Total observation period 4
BRCA2	9	31	5	160 (66–383)	0.64 (0.19–2.17)3	9	42	5	118 (49–283)	0.71 (0.2–2.54)3
sporadic	9	22	6	278 (125–618)	1	9	38	6	156 (70–347)	1

Abbreviations: N, number of patients; PYO, person-years of observation; Rec. rate, recurrence rate; Mort. Rate, mortality rate; HR, hazard ratio; 95% CI, 95% confidence interval; t, time point where HR switches from under to above 1 (in years of observation after diagnosis of epithelial ovarian cancer).

1 per 1000 PYO.

2 adjusted for debulking surgery (yes/no).

3 univariable analysis; adjusting for debulking surgery omitted due to zero patients without debulking surgery.

4 for the prospective analyses, the proportional hazard assumption is satisfied: no stratified Cox model necessary.

Fig 2

Kaplan-Meier survival curves for BRCA2-associated epithelial ovarian cancer (EOC) patients (dashed lines) and sporadic EOC patients (solid lines) treated with chemotherapy.

(A) progression-free survival and (B) overall survival for the complete dataset; (C) progression-free survival and (D) overall survival for the prospective dataset.

Discussion

In this retrospective matched cohort study, we confirmed better PFS during the first three years after EOC diagnosis and OS benefit during the first six years for patients with a BRCA1 or BRCA2 germline PV. After surviving this period, the benefit disappears, and might even turn into a higher risk of dying for gPV carriers. The observed survival benefit was slightly stronger for BRCA2 than for BRCA1.

Our results are in line with a number of previous studies. Studies with limited follow-up periods showed improved PFS and OS–with comparable periods without progression and time till death as seen in our study–for BRCA1-associated EOC patients [23], BRCA2-associated patients [23, 30], or combined BRCA1/2 cohorts [10, 22, 24–26]. Studies with long-term periods of follow-up showed that improved overall survival seems to be mainly driven by the first five years after diagnosis, with no benefit for those surviving that first period [31, 33, 36], or even worse OS afterwards [32], as observed in the current study.

Previously observed survival benefit could have been an age-effect. Recently, Mallen et al. observed worse survival for older patients, although the authors noted this may merely be the result of tumor biology rather than comorbidities [37]. As we currently matched–indirectly by matching on year of birth and year of diagnosis–on age at diagnosis, in contrast to most of the previous studies, our results support the suggestion that the observed difference is not related to age.

Our results support the hypothesis regarding BRCA1/2-associated EOC patients being more sensitive to platinum-based chemotherapy, especially since none of the patients in the current cohort received first-line maintenance treatment with a PARPi. Primary systemic treatment was not different for EOC patients with and without a BRCA1/2 germline gPV. Therefore, differences in PFS cannot be attributed to differences in received chemotherapy treatment, leaving gPV status as the most likely explanation. Although debulking surgery was performed in the vast majority of the patients (~95%), sporadic patients underwent less often debulking surgery, possibly due to a very poor prognosis of disease at diagnosis, or due to the presence of comorbidities. As this may indicate a higher baseline risk for death in the sporadic EOC groups, we adjusted the analyses for this variable.

In the recurrent setting BRCA-associated EOC patients were more often treated with chemotherapy, which may have influenced survival. The rationale for omitting systemic treatment may have been a worse clinical situation at presentation of recurrent disease, potentially resulting in a higher baseline risk of dying after recurrent EOC in the sporadic group. Further, in the BRCA groups more patients received PARPi after recurrent disease as a maintenance therapy. However, since PARPi has only been administered since 2015, the majority of the patients in the current cohort (approximately 95%) did not receive PARPi. For the sake of completeness, we performed subgroup analyses for OS excluding patients who were treated with PARPi in the recurrent setting and their matched counterparts. As none of the patients were treated with PARPi in the first-line, such subgroup analyses were not necessary for PFS. The subgroup analyses for OS revealed similar results as the original analyses (HR 0.81, 95% CI 0.68–0.97 for BRCA1 and HR 0.65, 95% CI 0.47–0.9 for BRCA2). Thus, the influence of PARPi in the recurrent setting is very limited in this study. This will increase, though, in future studies due to current clinical practice [38].

As previously described, including prevalent cases in studies involving BRCA gPV carriers can introduce seriously biased results [39, 40]. The majority of the gPV carriers in our cohort had their DNA tested after EOC diagnosis, with survival times up to 20 years until DNA test. Reassuringly, for the BRCA1 comparison, the additional prospective analyses showed comparable overall survival as for the complete analyses, suggesting minimal bias as a result from delayed DNA testing. Unfortunately, due to the small number of BRCA2 gPV carriers with a DNA test before cancer diagnosis, we were unable to draw meaningful conclusions from the prospective analyses among BRCA2 gPV carriers and matched sporadic patients. Alternatively, we performed left-truncated analyses with the observation for the BRCA groups starting at the date of either DNA test result or EOC diagnosis, whichever came last, thus excluding patients with recurrent disease, LFU or death before DNA test result. As shown in S2 Table, the results were comparable to those for the complete and prospective analyses, confirming minimal bias due to delayed DNA testing.

Other strengths of the current design include the separate BRCA1 and BRCA2 analyses, and the fact that we matched–indirectly by matching on year of birth and year of diagnosis–on age at diagnosis. The advantage of the latter is that also the sporadic EOC patients were relatively young at diagnosis. Therefore, we can reasonably assume that the leading cause of death is ovarian cancer in both groups, and that the mortality in the sporadic group is not distorted by competing causes of death due to older age.

One of the limitations of the study may be that not all sporadic patients were tested for a BRCA germline gPV. As mentioned before, the majority of the BRCA-associated EOC patients were tested after cancer diagnosis. Theoretically, the sporadic group may contain patients who were actually gPV carriers but never had the opportunity to get tested because they had died before DNA testing was performed or was even implemented in clinical practice. Unintentional misclassification of deceased patients in the sporadic groups may simultaneously overestimate the risk of dying in the sporadic groups and underestimate that risk in the BRCA groups, thus potentially overestimating the benefit for BRCA gPV carriers. Oppositely, the sporadic group may also include untested gPV carriers without recurrent disease or death, oppositely leading to an underestimation of the benefit. With regard to potential misclassification, we would like to emphasize that with the introduction of PARPi in 2015, more and more EOC patients undergo DNA testing sooner after diagnosis in order to receive the optimal treatment, at first only in the recurrent setting but nowadays also at primary disease.

In addition, data on somatic testing is not available for the current cohort. As a result, the sporadic group may contain a number of BRCA positive specimens, which may have influenced the results. However, as about only 5% of EOCs have a somatic BRCA pathogenic variant, we think this influence will be limited. Moreover, under the assumption that survival benefit will also apply to EOCs with a somatic BRCA pathogenic variant, potential misclassification of these EOCs in the sporadic group would led to an underestimation of the observed survival benefit on the short-term rather than an overestimation. Therefore, although the lack of data on somatic testing may be a deficiency in the study, in our opinion this may play a minor role.

Another limitation is the limited availability of data regarding complete debulking or residual disease after primary surgery in our study. In a previous study the only independent prognostic factor for survival in BRCA1/2 gPV carriers was the extent of debulking at primary surgery, with better survival for patients without macroscopic disease [10]. Recently, Ataseven et al. confirmed that complete macroscopic tumor resection is a strong prognostic factor in patients with EOC, regardless of BRCA status [26]. In the current study we did adjust for debulking surgery (yes/no), but the amount of residual disease may be more important in this respect. However, we found no differences between the comparison groups in the percentages of patients with residual disease for those patients with available data. Therefore, we expect no influence on the estimated HRs by adjusting for the amount of residual disease.

In conclusion, in this large case-matched cohort study we confirmed survival benefit for BRCA1/2-associated EOC patients treated with mainly platinum-based chemotherapy. This may indicate higher sensitivity to chemotherapy, both in the first-line and in the recurrent setting. The observed benefit appears to be limited to a relatively short period after EOC diagnosis. Future research is warranted to assess in more detail the added value of PARPi on both PFS and OS, especially on the long-term, where the benefit of classic systemic treatment seems to diminish and even disappear.

Patient and tumor characteristics–dataset for prospective analyses.

(DOCX)

Click here for additional data file.

Association of BRCA1 and BRCA2 germline pathogenic variant status with progression-free survival and overall survival for the left-truncated analyses.

(DOCX)

Click here for additional data file.

18 May 2022

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Reviewer #1: Thank you for the opportunity to review this very important analysis aiming to compare survival trajectory of women with ovarian cancer; with and without a germline BRCA mutation. The manuscript is well-written, the methodology is robust, and the analysis is of interest. However, there are a few factors that should be considered that the authors did not describe in detail, address, or account for. Considering the access to the detailed information for such an analysis is available to these authors, I suggest some of the key clinical and treatment variables are included to allow for a more robust analysis. In particular, route and timing of chemo and residual disease status following surgery. Some specific comments include:

1. Introduction: line 69: age-specific recommendations for preventive surgery is based on ages when risks start to increase; not really when childbearing is complete

2. Introduction: line 76: the authors did not include one of the largest, comprehensive analyses on the topic (PMID: 26556769).

3. Methods: line 106: the authors should consider refining the staging as a matching variable. Why were patients not matched by exact stage?

4. Methods; line 108: although clearly addressed in the limitations section of the discussion; this is a major limitation of this study. The sporadic cases were assumed to be negative for BRCA [or other HRD mutations]; which definitely resulted in misclassification of a proportion of these women who were included as the ‘control’ group.

5. Methods: line 134: ‘complete debulking surgery – yes/no’ is not an ideal classification of this very important predictor of prognosis. Ideally, the authors would have had classified this information according to size of residual disease following cytoreductive surgery … unless this indeed means NO or ZERO residual disease.

6. Methods: line 176 – the fact that there was a lot of missing data for the key prognostic variables is also problematic, in particular, residual disease.

7. Results: Table 1 should include overall survival from diagnosis to death

8. Results: Table 1 there is no information on route of chemotherapy; adjuvant vs. neoadjuvant, etc.

9. Results: Table 1 has no information on stage, histology, etc.

10. Results: although very few women used PARPs, perhaps a sensitivity analysis excluding these patients and running the key models would be a good idea.

11. Results: the inclusion of all stages and subtypes is a key limitation. Analyses should be stratified, at the very least, by stage ¾ OR high grade serous disease.

12. Discussion: the discussion is well done and the limitations are well described. Nevertheless, given there are other publications on the topic that allowed for a more robust statistical analysis on the topic.

Reviewer #2: Thank you for this important and well written paper. Though I am no expert on statistics, I thought your analysis was incredibly well thought out and thorough. The paper reads neatly and is easy to understand.

My critical feedback is as follows:

1. You mention that none of the sporadic OC specimens were tested for a somatic mutation. I feel the lack of somatic testing will include a number of BRCA positive specimens in the sporadic group, and will confound your results. I would like to see some attention paid to this in the confounders and discussion, as I think it is a major limitation of your study. I also think you should mention that these are germline mutations only in your abstract and introduction, as readers may now be accustomed to having EOC specimens tested and may assume all specimens are correctly classified before reading your statement on gremlin vs somatic testing.

2. The range of follow up includes 0.1 years. Did you consider a minimum amount of follow up time to include in the criteria (0.5y for example) to exclude the patients who died so early in their journey? At minimum did you match for death/recurrence at less than 6 mo as these outcomes are likely not in the spirit of your conclusions, which is to compare longer term outcomes?

3. Could you expand on censoring events in line 128? I am unclear what you mean by “another tumour” and wonder what you include here. Are metastasis included? Benign tumours?

4. Line 135 has a typographic error and should read “not confounding”

Thank you again for this excellent work. I look forward to its final acceptance.

**********

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11 Jul 2022

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We have addressed the requested prompt in the revised cover letter.

Additional Editor Comments:

The two reviewers nicely outlined the issues that need to be addressed in your manuscript before publishing it. Please do your best in addressing their comments and resubmit your revised manuscript for further consideration.

Response

We would like to thank both reviewers for their time and thorough and fair review of our manuscript.

Reviewer #1:

Thank you for the opportunity to review this very important analysis aiming to compare survival trajectory of women with ovarian cancer; with and without a germline BRCA mutation. The manuscript is well written, the methodology is robust, and the analysis is of interest. However, there are a few factors that should be considered that the authors did not describe in detail, address, or account for.

Considering the access to the detailed information for such an analysis is available to these authors, I suggest some of the key clinical and treatment variables are included to allow for a more robust analysis. In particular, route and timing of chemo and residual disease status following surgery.

Some specific comments include:

1. Introduction: line 69: age-specific recommendations for preventive surgery is based on ages when risks start to increase; not really when childbearing is complete

Response

We definitely agree with the reviewer that risk-reducing salpingo-oophorectomy is advised from specific ages, and not based on completeness of childbearing. We have rephrased the sentence on this topic in the Introduction (page 3; lines 69-72. Please note that pages and line numbers refer to the Revised Manuscript with Track Changes).

2. Introduction: line 76: the authors did not include one of the largest, comprehensive analyses on the topic (PMID: 26556769).

Response

According to the reviewer’s suggestion, we have included the study by Kotsopoulos et al. (reference number 29).

3. Methods: line 106: the authors should consider refining the staging as a matching variable. Why were

patients not matched by exact stage?

Response

Since BRCA1/2-associated ovarian cancer is usually diagnosed at considerable younger age than sporadic ovarian cancer, selecting a sufficient number of sporadic controls was difficult when matching on exact stage. Therefore, in consultation with the medical oncologist and in view of the different treatment indications for patients with lower and higher FIGO stages, we matched on the more rough categories of low (i.e. <= IIA) and high (i.e. >=IIB) FIGO stage. Reassuringly, as can be seen in the table below, there were no import differences between the comparison groups when looking at the exact FIGO stage, neither within the low grade categories nor in the high grade categories.

BRCA1 sporadic BRCA2 sporadic

N (%) N (%) p-value N (%) N (%) p-value

FIGO Low (≤IIA)

I 0 (0%) 5 (11%) 0.277 0 (0%) 2 (11%) 0.383

IA 7 (20%) 10 (22%) 5 (32%) 7 (36%)

IB 3 (9%) 3 (6%) 2 (12%) 0 (0%)

IC 18 (53%) 24 (52%) 7 (44%) 8 (42%)

IIA 6 (18%) 4 (9%) 2 (12%) 2 (11%)

FIGO High (≥IIB)

IIB 20 (6%) 25(8%) 0.053 5 (5%) 5 (6%) 0.086

IIC 25 (8%) 26 (8%) 3 (3%) 8 (9%)

III 9 (3%) 6 (2%) 6 (6%) 1 (1%)

IIIA 20 (6%) 15 (5%) 5 (5%) 2 (2%)

IIIB 45 (14%) 39 (13%) 12 (13%) 16 (18%)

IIIC 145 (45%) 168 (54%) 49 (51%) 51 (57%)

IV 59 (18%) 31 (10%) 16 (17%) 7 (8%)

Unknown 32 33 11 14

For the sake of readability, we omitted these numbers from the table for now, but when desired, we can add them either in the manuscript or as supplementary data.

4. Methods; line 108: although clearly addressed in the limitations section of the discussion; this is a major limitation of this study. The sporadic cases were assumed to be negative for BRCA [or other HRD mutations]; which definitely resulted in misclassification of a proportion of these women who were included as the ‘control’ group.

Response

We totally agree with the reviewer that the fact that not all sporadic patients were DNA tested is a limitation of the study. In addition to the considerations already addressed in the discussion (page 18; lines 286-294), we might speculate that with the same year of diagnosis and the same age at diagnosis – following from the matching criteria – the indication for DNA testing may have been the same for both groups. This may indicate that for sporadic patients with an indication for testing, indeed no BRCA mutation was found. Furthermore, the sporadic patients were in any case not included in the national Hereditary Breast and Ovarian Cancer Netherlands (HEBON) database, which may indicate at least a lack of family history of breast cancer or ovarian cancer. Still, these arguments do not completely rule out potential misclassification. Unfortunately, due to privacy laws and regulations we cannot retrieve and test tumor tissue of those patients who were not tested before.

5. Methods: line 134: ‘complete debulking surgery – yes/no’ is not an ideal classification of this very important predictor of prognosis. Ideally, the authors would have had classified this information according to size of residual disease following cytoreductive surgery … unless this indeed means NO or ZERO residual disease.

Response

‘Complete debulking surgery – yes/no’ indeed means the absence (‘yes’) or presence (‘no’) of any residual disease. For clarification, we have added this specification into the manuscript (page 6; line 136).

6. Methods: line 176 – the fact that there was a lot of missing data for the key prognostic variables is also problematic, in particular, residual disease.

Response

We totally agree with the reviewer that missing data on residual disease is a limitation of the study. However, as mentioned in the Discussion (page 19; lines 312-315), and as can be found in Table1 , we observed no differences between the comparison groups in the percentages of patients with residual disease for those patients with available data. As there seems no association for this variable with the exposure (i.e. carrying a germline BRCA pathogenic variant) in the current study population, the variable is no confounder according to the classical definition for confounders (i.e. being associated with the exposure and the outcome without being an intermediate factor), and therefore the variable does not have to be included in the multivariable model. In addition, although we realize we cannot be absolutely sure of this, we cannot think of a plausible reason to expect this distribution would be different among the patients with missing data, especially since the percentage of these patients is approximately the same in all groups (~30%). Therefore, we expect no influence on the estimated HRs by adjusting for the presence or absence of residual disease

7. Results: Table 1 should include overall survival from diagnosis to death

Response

We thank the reviewer for this suggestion and added the data into Table 1 and into Supplementary Table S1.

8. Results: Table 1 there is no information on route of chemotherapy; adjuvant vs. neoadjuvant, etc.

Response

We thank the reviewer for this suggestion and added the data into Table 1 and into Supplementary Table S1.

9. Results: Table 1 has no information on stage, histology, etc.

Response

Information on stage can be found above in our response on comment 3. As mentioned there, we omitted these numbers from the table for the sake of readability, but when desired, we can add them in. Following the reviewer’s suggestion, we have added the information on histology into Table 1 and into Supplementary Table S1.

10. Results: although very few women used PARPs, perhaps a sensitivity analysis excluding these patients and running the key models would be a good idea.

Response

Indeed, only a few women in this cohort were treated with PARP inhibitors (PARPi), and if so this was only done in the recurrent setting. Therefore, there is in our opinion no rationale to exclude patients who received PARPi after recurrent disease from the PFS analyses. Following the reviewer’s suggestion, we performed subgroup analyses for OS excluding patients who were treated with PARPi in the recurrent setting and their matched counterparts. The results can be found in the table below. The subgroup analyses for OS revealed similar results as the original analyses. We have added a few sentences regarding the subgroup analyses for OS to the Discussion (page 17; lines 261-265).

11. Results: the inclusion of all stages and subtypes is a key limitation. Analyses should be stratified, at the very least, by stage 3-4 OR high grade serous disease.

Response

In our opinion, the inclusion of all stages and subtypes is no limitation but rather a reflection of reality. In addition, since the distribution of low and high FIGO stages is not different between the comparison groups (due to the matching procedure), there is no need to adjust for this variable in the multivariable analyses. To inform the reviewer, we performed subgroup analyses including only those patients and their matched counterparts with FIGO stage 3 or 4. The results can be found in the table below. The proportional hazard assumption was violated only for the overall survival analysis comparing BRCA1 gPV carriers with sporadic patients. For the other analyses, stratification by time was not necessary and survival was in favor of the BRCA gPV carriers during the whole observation period. As one can see, the results point in the same direction as the original analyses, with slightly stronger hazard ratios.

HR (95% CI)

BRCA1 versus sporadic BRCA2 versus sporadic

Progression-free survival 0.75 (0.61-0.92) 0.46 (0.31-0.67)

Overall survival 0.65 (0.53-0.81) 0.42 (0.28-0.62)

Observation period < 5.1 years 0.56 (0.44-0.72)

Observation >= 5.1 years 0.98 (0.64-1.49)

12. Discussion: the discussion is well done and the limitations are well described. Nevertheless, given there are other publications on the topic that allowed for a more robust statistical analysis on the topic.

Response

We thank the reviewer for the kind words regarding the discussion. Indeed, there are other publications on the topic, although only a few have stratified the analyses by observation time or performed separate BRCA1 and BRCA2 analyses.

Reviewer #2:

Thank you for this important and well written paper. Though I am no expert on statistics, I thought your analysis was incredibly well thought out and thorough. The paper reads neatly and is easy to understand.

My critical feedback is as follows:

1. You mention that none of the sporadic OC specimens were tested for a somatic mutation. I feel the lack of somatic testing will include a number of BRCA positive specimens in the sporadic group, and will confound your results. I would like to see some attention paid to this in the confounders and discussion, as I think it is a major limitation of your study. I also think you should mention that these are germline mutations only in your abstract and introduction, as readers may now be accustomed to having EOC specimens tested and may assume all specimens are correctly classified before reading your statement on germline vs somatic testing.

Response

We agree with the reviewer that due to the lack of somatic testing the sporadic group may contain a number of BRCA positive specimens. Indeed, this may have influenced the results, although we think this influence will be limited, as about only 5% of EOCs have a somatic BRCA pathogenic variant. In addition, under the assumption that survival benefit will also apply to EOCs with a somatic BRCA pathogenic variant, potential misclassification of these EOCs in the sporadic group would led to an underestimation of the observed survival benefit rather than an overestimation. Therefore, although we agree that the lack of data on somatic testing may be a deficiency in the study, in our opinion this may play a minor role. We have added a paragraph in the Discussion on this topic (pages 18-19; lines 298-305).

To clarify more that the BRCA-deficient groups contain only patients with a germline pathogenic variant, we have mentioned this more specific in the abstract and the manuscript (page 2; lines 36, 41 & 55. page 4; line 87. Page 14; line 220. Page 15; line 225). Furthermore, to make this even more clear, we have replaced the abbreviation PV with gPV throughout the manuscript.

2. The range of follow up includes 0.1 years. Did you consider a minimum amount of follow up time to include in the criteria (0.5y for example) to exclude the patients who died so early in their journey? At minimum did you match for death/recurrence at less than 6 mo as these outcomes are likely not in the spirit of your conclusions, which is to compare longer term outcomes?

Response

As previous studies reported different short-term and long-term survival rates for gPV carriers, we were highly interested whether this also applied for our cohort. For this reason, we deliberately included patients who died early after diagnosis. Exclusion or matching these patients would have biased the survival rates for the short-term analyses.

3. Could you expand on censoring events in line 128? I am unclear what you mean by “another tumour” and wonder what you include here. Are metastasis included? Benign tumours?

Response

We considered only malignant tumors as another tumor. The date of the first recurrence defines the endpoint of the PFS analysis, and therefore metastases are not considered as censoring events nor as another tumor. To clarify the definition of the censoring events, we rephrased ‘another tumor’ into ‘a new primary malignant tumor’ (page 6; line 131).

4. Line 135 has a typographic error and should read “not confounding”

Response

We have corrected the typographic error (page 6; line 138).

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

9 Sep 2022

Progression-free survival and overall survival after BRCA1/2-associated epithelial ovarian cancer: a matched cohort study

PONE-D-22-08760R1

Dear Dr. Heemskerk-Gerritsen,

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

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Mohammad R. Akbari

Academic Editor

PLOS ONE

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

Reviewer #1: All comments have been addressed

**********

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

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

Reviewer #1: Yes

**********

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

Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: No

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13 Sep 2022

PONE-D-22-08760R1

Progression-free survival and overall survival after BRCA1/2-associated epithelial ovarian cancer: a matched cohort study

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