ORIGINAL PAPER
Nagoya J. Med. Sci. 83. 773–785, 2021
doi:10.18999/nagjms.83.4.773

Is area under the curve the best parameter for carboplatin
induced emetic risk stratification?
Sachiko Ozone1, Kazuya Ichikawa2, Masahiro Morise1, Akira Matsui1,
Fumie Kinoshita3, Reiko Matsuzawa1, Junji Koyama1, Ichidai Tanaka1
and Naozumi Hashimoto1
Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan2
Department of Pharmacy, Nagoya University Hospital, Nagoya, Japan
Data Coordinating Center, Department of Advanced Medicine, Nagoya University Hospital, Nagoya, Japan1

3

ABSTRACT
Carboplatin (CBDCA)-induced emetic risk is currently classified on the basis of CBDCA-area under
the curve (CBDCA-AUC). We investigated the utility of three CBDCA dosage parameters for predicting
emesis by CBDCA. Patients with thoracic cancer treated with CBDCA were included. The endpoints werecomplete response (CR) and total control (TC). CR was defined as no vomiting and no use of rescue
medication during the overall assessment period, whereas TC was defined as no vomiting, nausea, nor
use of rescue medication during the overall assessment period. The parameters of CBDCA were defined
as follows: (1) CBDCA-AUC; (2) CBDCA/body surface area (BSA): the administered dose of CBDCA
per body surface area (mg/m2); and (3) total CBDCA/body: the total administered dose of CBDCA (mg).
Eighty-five patients were evaluated. The median CBDCA/BSA but not CBDCA-AUC was higher in patientswith non-CR compared to those with CR. Receiver operating characteristic curve analysis revealed that
the AUC of CBDCA/BSA for predicting non-CR was higher than that of CBDCA-AUC. CBDCA/BSA
shows greater potential for predicting CBDCA-induced emetic risk compared with CBDCA-AUC, whichis the parameter in current antiemetic guidelines.
Keywords: carboplatin, chemotherapy-induced nausea and vomiting (CINV), moderate emetic risk
regimen, antiemetic treatment, antiemetic guideline recommendations
Abbreviations:
AUC: area under the curve
BSA: body surface area
CBDCA: carboplatin
CI: confidence interval
CINV: chemotherapy-induced nausea and vomiting
CR: complete response
eGFR: estimated glomerular filtration rate
MIC: minimum inhibitory concentration
NK1: neurokinin-1
OR: odds ratio
ROC: receiver operating characteristic
TC: total control

Received: November 12, 2020; accepted: March 22, 2021
Corresponding Author: Masahiro Morise, MD, PhD
Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho,Showa-ku, Nagoya 466-8550, Japan
Tel: +81-52-744-2167, Fax: +81-52-744-2176, E-mail: morisem@med.nagoya-u.ac.jp
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This is an Open Access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
License. To view the details of this license, please visit (http://creativecommons.org/licenses/by-nc-nd/4.0/).

INTRODUCTION
Despite the development of molecular targeted therapies, such as epidermal growth factor
receptor (EGFR) kinase inhibitors for EGFR-mutated non-small cell lung cancer, platinumcompounds remain key anticancer agents in treating several advanced solid tumors.1-3 Amongthese, carboplatin (CBDCA)—a second-generation platinum agent—is widely used to treat lungcancer, gynecologic cancers, the head and neck cancer, and breast cancer, etc.4
Chemotherapy-induced nausea and vomiting (CINV) is one of the most common and important
adverse events in patients treated with CBDCA. CBDCA is categorized as either high-emetic-risk
chemotherapy when the CBDCA-area under the blood-concentration time curve (CBDCA-AUC)
is ≥4 (mg/ml·min), or moderate-emetic-risk chemotherapy (MEC) when the CBDCA-AUC is<4 (mg/ml·min) according to National Cancer Community Network (NCCN) guidelines. In theguidelines of the American Society of Clinical Oncology (ASCO) and European Society of
Medical Oncology (ESMO)/Multinational Association of Supportive Care in Cancer (MASCC),CBDCA is classified as a MEC.5-8 In the NCCN and ASCO guidelines, antiemetic strategies are
based on the CBDCA-AUC. Specifically, a triple-antiemetic strategy involving a neurokinin-1(NK1) receptor antagonist, a serotonin receptor antagonist, and dexamethasone is recommended
for patients undergoing treatment with CBDCA-AUC of ≥4, whereas the use of NK1 receptor
antagonists is unnecessary for patients undergoing treatment with CBDCA-AUC of <4.5 In
contrast, ESMO/MASCC guidelines recommend using this triple antiemetic strategy regardlessof the CBDCA-AUC.
The risk stratification of CBDCA-induced CINV based on CBDCA-AUC in these guidelines
is mainly based on expert consensus, and it is unclear whether the current cutoff value of 4 is
optimal. In fact, the dose adjustment procedure of CBDCA using AUC is based on a pharmacokinetic study that investigated the relationship between AUC and efficacy/myelosuppression but
not CINV.9 In the retrospective cohort study that investigated the efficacy and safety of CBDCA
plus pemetrexed regimen, similar incidence of nausea and vomiting was reported between patientstreated with CBDCA AUC ≥ 4 and those treated with CBDCA AUC < 4 (any grade: 63.3% and70.8%, p=0.325, according to the National Cancer Institute-Common Toxicity Criteria ver3.0).10
Furthermore, in terms of cisplatin, another platinum agent as well as CBDCA, the dose of
cisplatin per body surface area (BSA) was an independent risk factor for CINV. 11 However,the data regarding useful CBDCA dosage parameters for predicting CINV risk are insufficient.
Additionally, few studies have investigated the association between CBDCA-AUC and CINV.
Based on these backgrounds, we hypothesized that the dose of CBDCA per BSA (CBDCA/
BSA [mg/m2]) or total dose of CBDCA per body (total CBDCA /body) has better utility forpredicting CINV risk compared to CBDCA-AUC, which lead us to conduct the current retrospective cohort study. The aim of this study was to explore the optimal CBDCA parameter forpredicting the risk of CINV. In this study, we investigated the utility of three CBDCA dosage
parameters (CBDCA-AUC, CBDCA/BSA, total CBDCA/body) for predicting CINV.

MATERIALS AND METHODS
Study design and Patients
This study was a retrospective cohort study, which was approved by institutional review board

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The best parameter for CINV of CBDCA

of Nagoya University Hospital. We included all patients with thoracic malignant tumor such aslung cancer, thymic cancer who were treated with CBDCA-based therapy regimens from 2011
to 2014 in our hospital for this retrospective cohort study.
Data collection
Individual medical charts were retrospectively reviewed, and the following data were collected: age, sex, ECOG performance status (PS), history of alcohol consumption (habitual or
non-habitual), prophylactic antiemetic treatment (granisetron/aprepitant/dexamethasone [GAD]or palonosetron/dexamethasone [PD]), and combination agent with CBDCA (pemetrexed or an
agent other than pemetrexed). We adopted combination agent with CBDCA as a clinical factor
which possibly affect the emetic events such as nausea and vomiting based on previous evidence.
Concretely, previous reports showed pemetrexed plus CBDCA had higher risk of nausea andvomiting compared to paclitaxel plus CBDCA.12,13
The parameters of CBDCA were defined as follows: (1) CBDCA-AUC, the actual dose of
CBDCA divided by (25 + estimated glomerular filtration rate [eGFR]); (2) CBDCA/BSA, theadministered dose of CBDCA per BSA (mg/m2); (3) total CBDCA/body, the total administereddose of CBDCA (mg). To determine the total dose of CBDCA in our clinical practice, weestimated GFR using one of the following three methods: (i) eGFR, (ii) Cockcroft calculation
without calibration by +0.2 mg/dl of serum creatinine, or (iii) Cockcroft calculation with calibration by +0.2 mg/dl of serum creatinine.14 Therefore, we needed to calibrate the CBDCA-AUC ofeach patient to evaluate the association between CBDCA-AUC and CINV. We recalculated the
CBDCA-AUC for each patient using eGFR in patients whose GFR was estimated using method(ii) or (iii) as follows:
Total administered dose of CBDCA
CBDCA – AUC =                 (mg/ml·min)eGFR+25On the basis of this calibration, the CBDCA-AUC of each patient was calculated to the second
decimal place.
Outcomes and Endpoints
The data regarding severity of nausea (classified into four grades: none, mild, moderate, orsevere), the incidence of vomiting, and the use of rescue antiemetic drugs were retrospectively
reviewed for outcome analysis.
The endpoints were complete response (CR) and total control (TC) for the evaluation of CINV.
We monitored nausea and vomiting in the 5 days from the initiation of CBDCA therapy. CR was
defined as no vomiting and no use of rescue medication during the overall assessment period, andTC was defined as no vomiting, no nausea, and no use of rescue medication during the overall
assessment period. Patients who did not achieve CR/TC were categorized as non-CR/non-TC.
Statistical analysis
Data were analyzed using JMP version 13.0. We considered p values of <0.05 to indicate
statistical significance. Comparisons of two groups (CR/TC or non-CR/non-TC) were performed
using Fisher’s exact test or Wilcoxon rank sum test. The cutoff value for each parameter of
CBDCA was determined using the Youden index method in the receiver operating characteristic
curve (ROC) analysis. The odds ratio (OR) with 95% confidence interval (CI) for each CBDCA
parameter for CR or TC failure was evaluated using univariate and multivariate analyses with

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Sachiko Ozone et allogistic regression. The adjusted clinical factors were sex, which was confirmed as a robust risk
factor for emesis, and clinical factors with p < 0.10 using Fisher’s exact test.

RESULTS
Patient characteristics
A total of 85 patients were included in this study. The patient characteristics and CBDCA
parameters are presented in Table 1. The median age of our cohort was 67 years (range 27–80
years), and 43.5% of patients were men. The majority of patients had a good PS (PS0: 47.1%
and PS1: 47.1%). Of the total study cohort, 41.2% of patients had habitual alcohol consumption
and 11.8% received opioid treatment as supportive care at the time of starting CBDCA-based
chemotherapy. In terms of prophylactic antiemetic therapy, 30.6% of patients received GAD, and69.4% of patients received PD. We also found that 50.6% of patients received pemetrexed as
a combination agent of CBDCA. Regarding CBDCA parameters, the median of CBDCA-AUC,
CBDCA/BSA, and total CBDCA/body was 5.01 (range 1.90–7.01), 303 mg/m2 (range 114–431),
and 480 mg (range 193–810), respectively.

Table 1

Patient characteristics (n = 85)

Variables

No. of patients (%)

Age, median (range)Sex

67 (27–80)
Male

37 (43.5)

Female48 (56.5)

040 (47.1)

1

40 (47.1)

2

5 (5.9)

Alcohol consumption

Habitual

35 (41.2)

Non-habitual

50 (58.8)

Opioid userYes

10 (11.8)

No75 (88.2)

GAD

26 (30.6)

PD

59 (69.4)

Pemetrexed

43 (50.6)

Others42 (49.4)

ECOG PS

Prophylactic anti emetic treatment
Combination agent
Albumin (g/dl), median

3.7 (2.1–4.8)

CBDCA-AUC (mg·min/mL), median (range)

5.01 (1.90–7.01)

CBDCA/BSA (mg/m2), median (range)

303 (114–431)

Total CBDCA/body (mg), median (range)

480 (193–810)

ECOG PS: European Cooperative Oncology Group performance status
Others: paclitaxel, S1, and gemcitabine were included in others.
GAD: granisetron, aprepitant and dexamethasone
PD: palonosetron and dexamethasone
CBDCA: carboplatin
AUC: area under curve
BSA: body surface area

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The best parameter for CINV of CBDCA

Comparison of patient characteristics and CBDCA parameters between patients with CR andnon-CR
Table 2A shows patients characteristics and CBDCA parameters in relation to CR status.
The overall rate of CR was 72.9% (62 of 85). The difference in the rate of CR among patientstreated with pemetrexed and those treated with other agents was close to statistical significance(62.8% vs. 83.3%, p = 0.050), but other baseline characteristics were not statistically significantly
different between patients who achieved CR and those who did not.
The median CBDCA-AUC was similar between patients who did and did not achieve CR(4.94 (range 1.90–6.57) vs. 5.25 (range 4.12–7.01), p = 0.169), while the median CBDCA/BSA
and total CBDCA/body were statistically significantly higher in patient with non-CR comparedto those in patients with CR (339 mg/m2 (range 185–411) vs. 290 mg/m2 (range 114–431), p =0.011; 510 mg (range 300–670) vs. 455 mg (range 193–810), p=0.042).

Table 2A

Patient characteristics and CBDCA parameters according to CR achievement (n = 85)

No. of patientswith CR (%)
Age

≥67

Sex

Female
ECOG PS
Alcohol consumption

34 (75.6)

11 (24.4)<67

28 (70.0)

12 (30.0)Male

25 (67.6)

12 (32.4)

37 (77.1)

11 (22.9)

031 (77.5)

9 (22.5)

1–2

31 (68.9)

14 (31.1)

Yes

27 (77.1)

8 (22.9)

No

35 (70.0)

15 (30.0)

Opioid userYes

7 (70.0)

3 (30.0)No

55 (73.3)

20 (26.7)

Antiemetic drugs

GAD

21 (80.8)

5 (19.2)

PD

41 (69.5)

18 (30.5)

Albumin (g/dL)
Combination agent<3.7

28 (80.0)

7 (20.0)≥3.7

34 (68.0)

16 (32.0)

Pemetrexed

27 (62.8)

16 (37.2)

Othersp value
0.629
0.339
0.466
0.621
1.000
0.427
0.321
0.050

35 (83.3)

7 (16.7)

CBDCA-AUC (mg·min/mL), median (range)

4.94 (1.90–6.57)

5.25 (4.12–7.01)

0.169

2

CBDCA/BSA (mg/m ), median (range)

290 (114–431)

339 (185–411)

0.011†

Total CBDCA/body (mg), median (range)

455 (193–810)

510 (300–670)

0.042†

indicates statistical significance (p < 0.05).
ECOG PS: European Cooperative Oncology Group performance status
Others: paclitaxel, S1, and gemcitabine were included in others.
GAD: granisetron, aprepitant and dexamethasone
PD: palonosetron and dexamethasone
CBDCA: carboplatin
AUC: area under curve
BSA: body surface area
SD: standard division
CR: complete response
Non-CR: non-complete response†

No. of patientswith Non-CR (%)

778
Sachiko Ozone et alComparison of patient characteristics and CBDCA parameters between patients with TC andnon-TC
Table 2B shows the patient characteristics and CBDCA parameters according to TC achievement. The TC rate in our cohort was 65.9%, 56 of 85 patients achieved TC. There were nopatient characteristics which showed statistically significant difference between patient with TC
and those with non-TC.
In terms of CBDCA parameters, median of CBDCA-AUC was similar between patient with
TC and those with non-TC (4.94 (range 1.90–6.57) vs. 5.25 (range 4.12–7.01), p=0.080), while
total CBDCA/body and CBDCA/BSA were statistically significantly higher in patient with nonTC compared to those in patients with TC (345 mg/m2 (range 185–426) vs. 284 mg/m2 (range
114–431), p < 0.001; and 530 mg (range 300–698) vs. 450 mg (range 193–810), p=0.006).

Table 2B

Patient characteristics and CBDCA parameters according to TC achievement (n = 85)

No. of patientswith TC (%)
Age

≥67

Sex

Female
ECOG PS
Alcohol consumption

33 (73.3)

12 (26.7)<67

23 (57.5)

17 (42.5)Male

22 (59.5)

15 (40.5)

34 (70.8)

14 (29.2)

029 (72.5)

11 (27.5)

1–2

27 (60.0)

18 (40.0)

Yes

24 (68.6)

11 (31.4)

No

32 (64.0)

18 (36.0)

Opioid userYes

6 (60.0)

4 (40.0)No

50 (66.7)

25 (33.3)

Antiemetic drugs

GAD

18 (69.2)

8 (30.8)PD

38 (64.4)

21 (35.6)

Albumin (g/dL)
Combination agent<3.7

26 (74.2)

9 (25.7)≥3.7

30 (60.0)

20 (40.0)

Pemetrexed

24 (55.8)

19 (44.2)

Othersp value
0.170
0.357
0.258
0.817
0.729
0.805
0.245
0.067

32 (76.2)

10 (23.8)

CBDCA-AUC (mg·min/mL), median (range)

4.94 (1.90–6.57)

5.25 (4.12–7.01)

0.080

2

CBDCA/BSA (mg/m ), median (range)

284 (114–431)

345 (185–426)<0.001†

Total CBDCA/body (mg), median (range)

450 (193–810)

530 (300–698)

0.006†

indicates statistical significance (p < 0.05).
ECOG PS: European Cooperative Oncology Group performance status
Others: paclitaxel, S1, and gemcitabine were included in others.
GAD: granisetron, aprepitant and dexamethasone
PD: palonosetron and dexamethasone
CBDCA: carboplatin
AUC: area under curve
BSA: body surface area
SD: standard division
TC: total control
Non-TC: non-total control†

No. of patientswith Non-TC (%)

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The best parameter for CINV of CBDCA

ROC curve analysis of CBDCA parameters for predicting non-CR and non-TC
The ROC analyses for non-CR and non-TC are shown in Figure 1. Interestingly, the AUC of
CBDCA/BSA (0.680) and total CBDCA/body (0.644) for predicting non-CR were higher thanthat of CBDCA-AUC (0.598), although this was not statistically significant (p=0.293, p=0.513,
respectively). The optimal cut-off values for predicting non-CR, as determined using the Youden
index method, was 5.07 for CBDCA-AUC, 325 mg/m2 for CBDCA/BSA, and 500 mg/body for
total CBDCA/body (Figure 1A).
As well as the results of ROC analysis for predicting non-CR, the AUC of CBDCA-BSA(0.727) and total CBDCA/body (0.682) for predicting non-TC were higher than that of CBDCAAUC (0.616), although this was not statistically significant (p=0.105, p=0.291, respectively). The
optimal cut-off values for each CBDCA parameter for predicting non-TC, as determined by the
Youden index method, were 5.49 for CBDCA-AUC, 339 mg/m2 for CBDCA/BSA, and 500 mg/
body for total CBDCA/body (Figure 1B).
Fig. 1A

Fig. 1B

Fig. 1 The receiver operating characteristic curve (ROC) analysis for predicting non-complete response (CR)and non-total control (TC)
Fig. 1A:	The receiver operating characteristic curve (ROC) analysis of each carboplatin (CBDCA) parameters forpredicting patients with non-complete response (CR). The optimal cut off value is calculated by Youden
index methods.
Fig. 1B:	The receiver operating characteristic curve (ROC) analysis of each carboplatin (CBDCA) parameters
for predicting patients with non-total control (TC). The optimal cut off value is calculated by Youden
index methods.

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Sachiko Ozone et al

Figure 2 shows the rate of CR and TC between patients with high CBDCA parameters andthose with low CBDCA parameters according to the determined optimal cut-off values.
The CR rate was significantly higher among patients with low CBDCA/BSA (<325 mg/m2)
than those with high CBDCA/BSA (≥325 mg/m2) (84.0% vs. 57.1%, p = 0.012) (Figure 2A).
As well as CBDCA/BSA, the CR rate was significantly higher among patients with low total
CBDCA/body (<500 mg) than those with high total CBDCA/body (≥500 mg) (84.4% vs. 60.0%,
p = 0.015). In contrast, the CR rates of patients with low and high CBDCA-AUC (<5.07 and≥5.07, respectively) were not statistically significantly different (79.2% vs. 64.9%, p = 0.220).
Fig. 2A

Fig. 2B

Fig. 2 The rate of complete response (CR) and total control (TC)
Fig. 2A:	The rate of complete response (CR) in subgroup according to optimal cut-off value of each carboplatin(CBDCA) parameters. * indicates p value less than 0.05. N.S. indicates not significant.
Fig. 2B:	The rate of total control (TC) in subgroup according to optimal cut-off value of each carboplatin(CBDCA) parameters. ** indicates p value less than 0.01. N.S. indicates not significant.

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The best parameter for CINV of CBDCA

Similar to the results of the CR rate, the TC rate in patients with low CBDCA/BSA (<339
mg/m2) was statistically significantly higher compared to that in patients with high CBDCA/
BSA (≥339 mg/m2) (78.0% vs.38.5%, p=0.001) (Figure 2B). The TC rate was significantly
higher among patients with low total CBDCA/body (<500 mg) compared with those with hightotal CBDCA/body (≥500 mg) (80.0% vs. 50.0%, p = 0.006). In contrast, the TC rates among
patients with low and high CBDCA-AUC (<5.49 and ≥5.49, respectively) were not significantly
different (72.7% vs. 53.3%, p = 0.095).
Univariate and multivariate analyses of CBDCA parameters for predicting non-CR and non-TC
Based on the optimal cut off values determined by Youden index methods, we performed
univariate and logistic regression multivariate analysis for predicting non-CR and non-TC oneach CBDCA parameters.
Table 3A shows a univariate analysis and multivariate analyses for predicting non-CR. In
multivariate analysis, CBDCA/BSA (adjusted Odds (OR) 3.15 [95% confidence interval (CI):
1.08–9.16, p=0.035]) and total CBDCA/body (adjusted OR 3.04 [95% CI: 1.04–8.93], p=0.043)
were independent risk factors for predicting non-CR. In contrast, CBDCA-AUC (adjusted OR
1.78 [95% CI: 0.64–4.98, p=0.272]) was not statistically significant for predicting non-CR.

Table 3A

Univariate analysis and Multivariate analysis for non-CR (n = 85)

Univariate
analysis

Variables

OR (95% CI)
CBDCA-AUC (mg·min/mL) <5.07
CBDCA/BSA (mg/m )2

Total CBDCA/body (mg)Multivariate
analysis†p value1≥5.07

2.06 (0.78–5.43)

<325

1

≥325

3.94 (1.43–10.81)

<500

1

≥500

3.61 (1.30–10.08)

OR (95% CI)

p value1
0.145

1.78 (0.64–4.98)

0.272

1
0.008

††

3.15 (1.08–9.16)

0.035††

1
0.014

††

3.04 (1.04–8.93)

0.043††

OR: odds ratio†
OR were adjusted by sex and the combination of pemetrexed in multivariate analysis.
††
indicates statistical significance (p < 0.05).

Table 3B shows a univariate analysis and multivariate analyses for predicting non-TC. In
multivariate analysis, CBDCA/BSA (adjusted OR 4.63 [95% CI: 1.59–13.47, p=0.005]) andtotal CBDCA/body (adjusted OR 3.56 [95% CI: 1.30–9.76], p=0.014) were independent risk
factors for predicting non-TC. In contrast, CBDCA-AUC (adjusted OR 2.15 [95% CI: 0.80–5.76,
p=0.128]) was not statistically significant for predicting non-TC. Collectively, CBDCA-AUC was
not predictive for both non-CR and non-TC, while CBDCA/BSA and total CBDCA/body wereassociated with both non-CR and non-TC.

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Sachiko Ozone et al

Table 3B

Multivariate analysis for non-TC (n = 85)

Univariate
analysis

Variables

OR (95% CI)
CBDCA-AUC (mg·min/mL) <5.49
CBDCA/BSA (mg/m )2

Total CBDCA/body (mg)Multivariate
analysis†p value1

OR (95% CI)

p value1≥5.49

2.33 (0.92–5.92)

<339

1

≥339

5.66 (2.08–15.41)

<500

1

≥500

4.00 (1.53–10.43)

0.075

2.15 (0.80–5.76)

0.128

1
<0.001††

4.63 (1.59–13.47)

0.005††

1
0.005

††

3.56 (1.30–9.76)

0.014††

OR: odds ratio†
OR were adjusted by sex and the combination of pemetrexed in multivariate analysis.
††
indicates statistical significance (p < 0.05).

DISCUSSION
The current study demonstrates that CBDCA/BSA and total CBDCA/body, but not CBDCAAUC, are useful parameters for predicting the risk of CINV. To the best of our knowledge,
this is the first study to investigate the utility of these parameters as predicting factors for
CBDCA-induced nausea and vomiting.
The current antiemesis guidelines of ASCO and NCCN recommends that triple antiemetic
strategy with NK1 receptor antagonist, 5-HT3 receptor antagonist, and dexamethasone should beselected for patients treated with CBDCA-AUC ≥ 4.5,7,8 These recommendations are based on thefact that most phase III studies of triple antiemetic strategy for CBDCA regimen have included
only patients treated with CBDCA having AUC ≥4.15-18 Although the MASCC/ESMO guidelines
universally recommend triple antiemetic therapy for CBDCA-induced nausea and vomiting,5,6
few studies have demonstrated the benefits of such a strategy for patients with CBDCA-AUC<4. In fact, Jordan et al discussed this issue for patients treated with lower doses of CBDCA
in their systematic review of NK1 receptor antagonists.19 Besides these backgrounds, the ROC
analysis of CBDCA-AUC in the present study indicated AUC of 0.598 for predicting non-CR
and 0.616 for predicting non-TC, both of which would not be considered acceptable (AUC <0.7) in terms of statistical consensus.20
We found that CBDCA/BSA and total CBDCA/body have potential utility for predicting
CBDCA-induced nausea and vomiting; for CBDCA/BSA, the AUC of the ROC for predicting
non-TC was >0.7, which indicates good predictivity.20 In addition, the TC rate of patients received
CBDCA with ≥ 339 mg/m2 (optimal cut off value by Youden Index) was only 38.5%, and thosewould be a good target for triple antiemetic strategy. A pharmacokinetic study investigating
CBDCA treatment for patients with severe renal insufficiency could verify the results of thecurrent study. Oguri et al investigated carboplatin concentrations in plasma in patients with eGFR
< 30 ml/min/1.73 m2.21 Of these patients, target AUC were set as 4 or 5. However, any gradeof nausea or vomiting was not noted in their study. In patients with severe renal insufficiency(eGFR < 30 ml/min/1.73m2), total CBDCA/body must be below 275 mg with a target AUC of 5
because the estimated CBDCA clearance is equal to GFR (ml/min) + 25. The results of Oguri,
et al suggested the incidence of CBDCA-induced nausea and vomiting to be low in patients
receiving low total CBDCA/body with high CBDCA-AUC (4 or more). Consistent with these

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The best parameter for CINV of CBDCA

previous reports, our results suggest that the association between CBDCA-AUC and CBDCAinduced nausea and vomiting is weak and further studies are warranted to identify new usefulpredictors of CBDCA-induced nausea and vomiting. The reason of the superiority of CBDCA/
BSA to CBDCA-AUC is difficult to explain clearly.
However, we speculate that different mechanisms between the CBDCA-induced antitumor effectand CBDCA-induced emesis are a possible reason to explain the results of the current study.
CBDCA exerts antitumor efficacy by inducing DNA crosslinks, whereas CBDCA causes CINV
by increasing several cytokines such as substance P, resulting in stimulating neurokinin 1 (NK1)
receptor. The association between CBDCA-AUC and antitumor effects or myelosuppression iswell established by previous research, and both effects are induced by CBDCA-mediated DNA
crosslink formation.9 However, to our best knowledge, the association between the pharmacodynamics of CBDCA and CINV has not been investigated at this point. In antimicrobial research,several pharmacodynamic parameters are important for a given antibiotic agent, including (1) the
ratio of maximum serum concentration (Cmax) to the minimum inhibitory concentration (MIC);
Cmax/MIC, (2) the ratio of the AUC versus MIC; AUC/MIC, (3) the duration of the dosinginterval that plasma concentrations exceed the MIC; Time above MIC.22 These suggest that therelevant pharmacodynamic parameters predicting major effect or side effect of anticancer agentsare different depends on the mechanism of drug action. As mentioned above, the mechanism of
CINV caused by CBDCA is different from that of myelosuppression. Although pharmacodynamics
of CBDCA for predicting CINV is not elucidated, it is possible that Cmax of CBDCA rather
than AUC of CBDCA is the best pharmacodynamic parameters predicting CINV of CBDCA,
and the dose of CBDCA/BSA might be well associated with Cmax of CBDCA. Because all ofthese are only speculative, further studies are warranted for investigating an optimal parameterfor predicting CBDCA induced CINV.
Our study has several limitations, which should be acknowledged. The retrospective cohort
analysis was based on patients recruited from a single institution. The results of multivariate
analysis and optimal cut-off values for predicting non-CR and non-TC should be interpretedwith caution because overfitting bias could exist. Because of the retrospective nature, the event
rates for CR and TC in terms of vomiting and the use of rescue antiemetic drugs could beunderestimated. Therefore, future multi-center prospective studies are required to validate theresults of our study.
In conclusion, CBDCA/BSA shows greater potential than CBDCA-AUC for predicting the riskof CBDCA-induced emesis. Patients treated with high CBDCA/BSA may be good candidates fortriple antiemetic therapy, regardless of CBDCA-AUC, whereas those receiving low CBDCA/BSA
may not require NK1 receptor antagonists, even when the CBDCA-AUC is ≥4.

AUTHOR CONTRIBUTIONS
S.O. and K.I. equally contributed to this work.

CONFLICTS OF INTEREST
All authors declare no conflict interest in regard to the current study.

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Sachiko Ozone et al

SOURCE OF FUNDING
Not declared.

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